http://wiki.isikhnas.com/api.php?action=feedcontributions&user=Angus&feedformat=atomWiki Sumber Informasi iSIKHNAS - User contributions [en]2024-03-28T18:59:07ZUser contributionsMediaWiki 1.31.16http://wiki.isikhnas.com/index.php?title=Drug_Codes:_Obat_tradisional%26action%3Dedit&diff=39234Drug Codes: Obat tradisional&action=edit2017-02-09T07:58:42Z<p>Angus: </p>
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<div>{{#apGetSQL:select code, name from drugs where drugtypeid = 16 and not del order by left(code,1),substring(code,2,10)::integer |Code, Nama Obat}}</div>Angushttp://wiki.isikhnas.com/index.php?title=Drug_Codes:_Obat_tradisional%26action%3Dedit&diff=39233Drug Codes: Obat tradisional&action=edit2017-02-09T07:50:35Z<p>Angus: </p>
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<div>{{#apGetSQL:select name, code from drugs where drugtypeid = 16 and not del |Code, Nama Obat}}</div>Angushttp://wiki.isikhnas.com/index.php?title=Drug_Codes:_Obat_tradisional%26action%3Dedit&diff=39232Drug Codes: Obat tradisional&action=edit2017-02-09T07:49:33Z<p>Angus: Created page with "{{#apGetSQL:select 1,2 from drugs where drugtypeid = 15 and not del order by left(code,1),substring(code,2,10)::integer |Code, Nama Obat}}"</p>
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<div>{{#apGetSQL:select 1,2 from drugs where drugtypeid = 15 and not del order by left(code,1),substring(code,2,10)::integer |Code, Nama Obat}}</div>Angushttp://wiki.isikhnas.com/index.php?title=Database_erds&diff=39180Database erds2016-05-03T16:43:56Z<p>Angus: </p>
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<div>= Entity-relationship diagrams =<br />
These diagrams illustrate the main relationships between database tables for the key modules. <br />
<br />
==Abattoir reporting==<br />
[[File:abattoir_erd.svg|800px]]<br />
<br />
==User access==<br />
[[File:access_erd.svg|800px]]<br />
<br />
==Animal identification==<br />
[[File:animal_id_erd.svg|800px]]<br />
<br />
==Culling==<br />
[[File:culling_erd.svg|800px]]<br />
<br />
==Excel import==<br />
[[File:excel_import.svg|800px]]<br />
<br />
==Disease investigation==<br />
[[File:investigation.svg|800px]]<br />
<br />
==Laboratory==<br />
[[File:lab_erd.svg|800px]]<br />
<br />
==Animal movement==<br />
[[File:movement_erd.svg|800px]]<br />
<br />
==Other control activities==<br />
[[File:other_control_activities_erd.svg|800px]]<br />
<br />
==Population==<br />
[[File:population_erd.svg|800px]]<br />
<br />
==Reports==<br />
[[File:reports_erd.svg|800px]]<br />
<br />
==Routine disease reporting==<br />
[[File:routine_disease_erd.svg|800px]]<br />
<br />
==SMS System==<br />
[[File:sms_erd.svg|800px]]<br />
<br />
==Surveillance==<br />
[[File:surveillance_erd.svg|800px]]<br />
<br />
==Training==<br />
[[File:training_erd.svg|800px]]<br />
<br />
==URL Import==<br />
[[File:url_import_erd.svg|800px]]<br />
<br />
==Vaccination==<br />
[[File:vaccination_erd.svg|800px]]</div>Angushttp://wiki.isikhnas.com/index.php?title=Database_erds&diff=39179Database erds2016-05-03T16:42:24Z<p>Angus: </p>
<hr />
<div>= Entity-relationship diagrams =<br />
These diagrams illustrate the main relationships between database tables for the key modules. <br />
<br />
==Abattoir reporting==<br />
[[File:abattoir_erd.svg|800px]]<br />
<br />
==User access==<br />
[[File:access_erd.svg|800px]]<br />
<br />
==Animal identification==<br />
[[File:animal_id_erd.svg|800px]]<br />
<br />
==Culling==<br />
[[File:culling_erd.svg|800px]]<br />
<br />
==Excel import==<br />
[[File:excel_import.svg|800px]]<br />
<br />
==Disease investigation==<br />
[[File:investigation.svg|800px]]<br />
<br />
==Laboratory==<br />
[[File:lab_erd.svg|800px]]<br />
<br />
==Animal movement==<br />
[[File:movement_erd.svg]]<br />
<br />
==Other control activities==<br />
[[File:other_control_activities_erd.svg]]<br />
<br />
==Population==<br />
[[File:population_erd.svg]]<br />
<br />
==Reports==<br />
[[File:reports_erd.svg]]<br />
<br />
==Routine disease reporting==<br />
[[File:routine_disease_erd.svg]]<br />
<br />
==SMS System==<br />
[[File:sms_erd.svg]]<br />
<br />
==Surveillance==<br />
[[File:surveillance_erd.svg]]<br />
<br />
==Training==<br />
[[File:training_erd.svg]]<br />
<br />
==URL Import==<br />
[[File:url_import_erd.svg]]<br />
<br />
==Vaccination==<br />
[[File:vaccination_erd.svg]]</div>Angushttp://wiki.isikhnas.com/index.php?title=File:Vaccination_erd.svg&diff=39178File:Vaccination erd.svg2016-05-03T16:39:00Z<p>Angus: </p>
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<div></div>Angushttp://wiki.isikhnas.com/index.php?title=File:Url_import_erd.svg&diff=39177File:Url import erd.svg2016-05-03T16:38:24Z<p>Angus: </p>
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<div></div>Angushttp://wiki.isikhnas.com/index.php?title=File:Training_erd.svg&diff=39176File:Training erd.svg2016-05-03T16:37:48Z<p>Angus: </p>
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<div></div>Angushttp://wiki.isikhnas.com/index.php?title=File:Surveillance_erd.svg&diff=39175File:Surveillance erd.svg2016-05-03T16:37:17Z<p>Angus: </p>
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<div></div>Angushttp://wiki.isikhnas.com/index.php?title=File:Sms_erd.svg&diff=39174File:Sms erd.svg2016-05-03T16:36:45Z<p>Angus: </p>
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<div></div>Angushttp://wiki.isikhnas.com/index.php?title=File:Routine_disease_erd.svg&diff=39173File:Routine disease erd.svg2016-05-03T16:35:47Z<p>Angus: </p>
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<div></div>Angushttp://wiki.isikhnas.com/index.php?title=File:Reports_erd.svg&diff=39172File:Reports erd.svg2016-05-03T16:34:44Z<p>Angus: </p>
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<div></div>Angushttp://wiki.isikhnas.com/index.php?title=File:Population_erd.svg&diff=39171File:Population erd.svg2016-05-03T16:33:52Z<p>Angus: </p>
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<div></div>Angushttp://wiki.isikhnas.com/index.php?title=File:Other_control_activities_erd.svg&diff=39170File:Other control activities erd.svg2016-05-03T16:33:19Z<p>Angus: </p>
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<div></div>Angushttp://wiki.isikhnas.com/index.php?title=File:Movement_erd.svg&diff=39169File:Movement erd.svg2016-05-03T16:32:40Z<p>Angus: </p>
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<div></div>Angushttp://wiki.isikhnas.com/index.php?title=File:Lab_erd.svg&diff=39168File:Lab erd.svg2016-05-03T16:30:30Z<p>Angus: </p>
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<div></div>Angushttp://wiki.isikhnas.com/index.php?title=Database_erds&diff=39167Database erds2016-05-03T16:29:56Z<p>Angus: </p>
<hr />
<div>= Entity-relationship diagrams =<br />
These diagrams illustrate the main relationships between database tables for the key modules. <br />
<br />
==Abattoir reporting==<br />
[[File:abattoir_erd.svg]]<br />
<br />
==User access==<br />
[[File:access_erd.svg]]<br />
<br />
==Animal identification==<br />
[[File:animal_id_erd.svg]]<br />
<br />
==Culling==<br />
[[File:culling_erd.svg]]<br />
<br />
==Excel import==<br />
[[File:excel_import.svg]]<br />
<br />
==Disease investigation==<br />
[[File:investigation.svg]]<br />
<br />
==Laboratory==<br />
[[File:lab_erd.svg]]<br />
<br />
==Animal movement==<br />
[[File:movement_erd.svg]]<br />
<br />
==Other control activities==<br />
[[File:other_control_activities_erd.svg]]<br />
<br />
==Population==<br />
[[File:population_erd.svg]]<br />
<br />
==Reports==<br />
[[File:reports_erd.svg]]<br />
<br />
==Routine disease reporting==<br />
[[File:routine_disease_erd.svg]]<br />
<br />
==SMS System==<br />
[[File:sms_erd.svg]]<br />
<br />
==Surveillance==<br />
[[File:surveillance_erd.svg]]<br />
<br />
==Training==<br />
[[File:training_erd.svg]]<br />
<br />
==URL Import==<br />
[[File:url_import_erd.svg]]<br />
<br />
==Vaccination==<br />
[[File:vaccination_erd.svg]]</div>Angushttp://wiki.isikhnas.com/index.php?title=File:Investigation.svg&diff=39166File:Investigation.svg2016-05-03T16:26:42Z<p>Angus: </p>
<hr />
<div></div>Angushttp://wiki.isikhnas.com/index.php?title=File:Excel_import.svg&diff=39165File:Excel import.svg2016-05-03T16:25:58Z<p>Angus: </p>
<hr />
<div></div>Angushttp://wiki.isikhnas.com/index.php?title=File:Culling_erd.svg&diff=39164File:Culling erd.svg2016-05-03T16:25:27Z<p>Angus: </p>
<hr />
<div></div>Angushttp://wiki.isikhnas.com/index.php?title=File:Animal_id_erd.svg&diff=39163File:Animal id erd.svg2016-05-03T16:24:58Z<p>Angus: </p>
<hr />
<div></div>Angushttp://wiki.isikhnas.com/index.php?title=File:Access_erd.svg&diff=39162File:Access erd.svg2016-05-03T16:24:31Z<p>Angus: </p>
<hr />
<div></div>Angushttp://wiki.isikhnas.com/index.php?title=Database_erds&diff=39161Database erds2016-05-03T16:24:03Z<p>Angus: </p>
<hr />
<div>= Entity-relationship diagrams =<br />
These diagrams illustrate the main relationships between database tables for the key modules. <br />
<br />
==Abattoir reporting==<br />
[[File:abattoir_erd.svg]]<br />
<br />
==User access==<br />
[[File:access_erd.svg]]<br />
<br />
==Animal identification==<br />
[[File:animal_id_erd.svg]]<br />
<br />
==Culling==<br />
[[File:culling_erd.svg]]<br />
<br />
==Excel import==<br />
[[File:excel_import.svg]]<br />
<br />
==Disease investigation==<br />
[[File:investigation.svg]]</div>Angushttp://wiki.isikhnas.com/index.php?title=File:Abattoir_erd.svg&diff=39160File:Abattoir erd.svg2016-05-03T16:21:13Z<p>Angus: </p>
<hr />
<div></div>Angushttp://wiki.isikhnas.com/index.php?title=Database_erds&diff=39159Database erds2016-05-03T16:20:25Z<p>Angus: Created page with "== Entity-relationship diagrams == File:abattoir_erd.svg"</p>
<hr />
<div>== Entity-relationship diagrams ==<br />
[[File:abattoir_erd.svg]]</div>Angushttp://wiki.isikhnas.com/index.php?title=MediaWiki:Sidebar&diff=39158MediaWiki:Sidebar2016-05-03T16:18:46Z<p>Angus: </p>
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<div>* navigation<br />
** mainpage|Home|#home#<br />
** ISIKHNAS_User_References|Pengguna : Users|#userreferences#<br />
** Technical References|Teknis : Technical|#techreferences#<br />
** Training|Pelatihan : Training|#trainingresources#<br />
** Communication|Komunikasi : Communication|#communication#<br />
** FAQ: Frequently Asked Questions|Pertanyaan : FAQ|#FAQ#<br />
<br />
* #home#<br />
** What_is_iSIKHNAS?|Apa itu ISIKHNAS? : What is iSIKHNAS?<br />
** FAQ:Frequently Asked Questions|FAQ:Pertanyaan Umum : FAQ<br />
** ISIKHNAS_code_lists|ISIKHNAS Kode-Kode : Codes<br />
<br />
* #userreferences#<br />
** Manuals:Village_Reporters#User_Guide_for_Village_Reporters_.28Pelsa.29|Pelsa : Village reporters<br />
** Manuals_for_Field_Data_Reporters|Dinas : Field Staff<br />
** Manuals_for_Laboratory_Users|Laboratorium : Laboratory<br />
** Manual_for_Coordinators|Koordinator : Coordinators<br />
** Manuals_for_Data_Users|Pengguna Data : Data Users<br />
<br />
* #techreferences#<br />
** Overview_of_data_managed|Data Dikelola : Data managed<br />
** Technical_references|Referensi Teknis : Technical references<br />
** ISIKHNAS_code_lists|Kode-kode : Codes<br />
** Database_tables|Tabel Database : Database Tables<br />
** Database_erds|Struktur Database : Database ERDs<br />
** Database_functions|Fungsi Database : Database Functions<br />
** Technical_References#Guides_and_standards|Panduan dan Standar : Guides and Standards<br />
** Technical_References#Wiki|Menggunakan wiki : Using the Wiki<br />
<br />
* #trainingresources#<br />
** ISIKHNAS_Training_Resources#ISIKHNAS Training Centre|ISIKHNAS pelatihan pengguna : iSIKHNAS Training<br />
** Field Epidemiology/id|Epidemiologi di lapangan : Field Epidemiology<br />
** Surveillance/id|Surveilans : Surveillance<br />
** Budget Advocacy/id|Advokasi untuk Anggaran : Budget Advocacy<br />
** Epidemiological Data Analysis|Analisis Epidemiologi data : Epi Data Analysis<br />
** GIS for Animal Health/id|GIS untuk kesehatan hewan : GIS for animal health<br />
** Excel/id|Excel<br />
** Disease Investigation/id|Investigasi penyakit untuk paravet : Disease Investigation<br />
** Recognising_Signs_of_Poor_Health/id|Mengenali tanda-tanda penyakit : Recognising Signs of Disease<br />
** Facilitation Guide/id|Panduan fasilitasi : Facilitators Manual<br />
** Glossary of Terms/id|Glosarium : Glossary<br />
<br />
* #communication#<br />
** Communication#Preparation_for_Socialising_iSIKHNAS|Sosialisasi ISIKHNAS : Communicating about iSIKHNAS<br />
** Communication#iSIKHNAS_Videos|ISIKHNAS Videos<br />
** Communication#ISIKHNAS Logos|ISIKHNAS Logos<br />
<br />
* #FAQ#<br />
** FAQ:_Frequently_Asked_Questions/id#About_iSIKHNAS|Informasi tentang ISIKHNAS : About iSIKHNAS<br />
** FAQ:_Frequently_Asked_Questions/id#Mengirimkan_data|Menyerahkan data : Submitting data<br />
** FAQ:_Frequently_Asked_Questions/id#Mendapatkan_informasi_dari_sistem|Menggunakan kode : Using system queries<br />
<br />
<br />
* SEARCH<br />
* TOOLBOX<br />
* LANGUAGES</div>Angushttp://wiki.isikhnas.com/index.php?title=File:ISIKHNAS_app_2016-03-04.apk&diff=39153File:ISIKHNAS app 2016-03-04.apk2016-03-04T10:03:34Z<p>Angus: iSIKHNAS Mobile App</p>
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<div>iSIKHNAS Mobile App</div>Angushttp://wiki.isikhnas.com/index.php?title=Mobile_App&diff=39152Mobile App2016-03-04T10:02:47Z<p>Angus: /* Download */</p>
<hr />
<div>==Modul 19: iSIKHNAS Mobile App ==<br />
[[File:App.png|80px|left]]<br />
<br />
''Bahasa Indonesia''<br />
<br />
'''Ini sedang dikembangkan'''<br />
Sistem ini masih dalam pengembangan, dan versi yang saat ini tersedia hanya bukti-of-konsep. Ini akan diperbarui bila siap untuk penggunaan umum.<br />
<br />
iSIKHNAS Mobile App akan memungkinkan pengguna terdaftar untuk menulis pesan SMS menggunakan bentuk interaktif pada ponsel Android pintar mereka. Ini berarti bahwa Anda tidak perlu mengingat format pesan, atau salah satu kode pesan. Pesan itu masih dikirim melalui SMS, sehingga Anda tidak perlu koneksi internet di lapangan untuk mengirim pesan.<br />
<br />
''English''<br />
<br />
'''This system is still under development,''' and the version that is currently available is only a proof-of-concept. It will be updated when it is ready for general use.<br />
<br />
The iSIKHNAS Mobile App will allow registered users to compose SMS messages using an interactive form on their Android smart phone. This means that you won't have to remember the message format, or any of the message codes. The message is still sent by SMS, so you won't need an internet connection in the field to send the message.<br />
<br />
===Download===<br />
To test the system you can download this test version for your handphone [[Media:iSIKHNAS_app_2016-03-04.apk|'''HERE''']].<br />
<br />
===Materi Pelatihan===<br />
Ini sedang dikembangkan<br />
<br />
===Bahan Tambahan===<br />
[[File:Nuvola apps kpager.png|60px|left]]<br />
*[[Media:iSIKHNAS mobile app v1.pptx|APLIKASI telepon genggam iSIKHNAS]]<br />
<br />
<br />
===Panduan Pengguna===<br />
Ini sedang dikembangkan</div>Angushttp://wiki.isikhnas.com/index.php?title=Epidemiological_Data_Analysis&diff=39103Epidemiological Data Analysis2015-12-02T08:34:42Z<p>Angus: Marked this version for translation</p>
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<div><languages/><br />
<translate><br />
==Data analysis using iSIKHNAS data case studies== <!--T:1--><br />
[[File:Autoship1256.png|120px|left]]<br />
<br />
<br />
<br />
=== Pre-requisites === <!--T:2--><br />
This course is for veterinarians within the Indonesian animal health system. It is assumed that participants will have completed the ''Excel'', ''Basic Field Epidemiology'' and ''Surveillance'' training modules before this course. If you already know about epidemiology and how to use Excel, then these pre-requisite modules are not required.<br />
<br />
=== Objectives of course === <!--T:3--><br />
[[File:Target colour.jpg|60px|left]]<br />
<br />
<!--T:4--><br />
The broader aim of the course is help participants make evidence based animal health policy decisions. This will assist them to improve livestock production and health in Indonesia. <br />
<br />
<!--T:5--><br />
To do this, participants need to be able to access, understand and analyse information on animal health in Indonesia. Fortunately, a new initiative in Indonesia means that Indonesian animal health staff has access to one of the best animal health information systems in the world: iSIKHNAS. This provides staff with large amounts of high quality information (data<ref name="ftn1">The Oxford dictionary definition of data is: Facts and statistics collected together for reference or analysis</ref>) that they can use to make good animal health decisions. Therefore, the objectives of this course are to teach participants to download, understand, evaluate, analyse and interpret iSIKHNAS data. <br />
<br />
=== Learning approach === <!--T:6--><br />
[[File:Nuvola apps edu miscellaneous.png|60px|left]]<br />
<br />
<!--T:7--><br />
This course will be taught by analysing real iSIKHNAS data. Three case studies will be presented. During each case study, a question will be asked. Then the question will be answered by participants during practical exercises. Spaces are included after each exercise where you can write your answers. Answers to exercises are provided as Appendix 2. It is generally recommended that you answer the question before reading the answers. <br />
<br />
<!--T:8--><br />
Sometimes, notes on core concepts will be presented before or during case studies to support learning. These are backgrounded with grey to enable you to distinguish these notes from the exercises. <br />
<br />
<!--T:9--><br />
The course is very applied and relevant to Indonesian animal health staff. The three case studies concentrate on: assessment of veterinary services (staff performance), disease management (diarrhoea in cattle) and livestock production (beef self-sufficiency). <br />
<br />
<!--T:10--><br />
The data used in this training course was downloaded in early 2014. This was when iSIKHNAS had been operating for approximately a year in a small part of Indonesia. This early data was used so that we could provide answers to exercises. You may wish to download newer and more complete data to analyse during exercises at the time of your course. Please be aware that if you do, you will not have answers to check your work. <br />
<br />
<!--T:11--><br />
The interim nature of the data means that no real conclusions can be made about the results of data-analyses conducted during this course. Instead, we conducted the analyses and made conclusions to demonstrate and teach data analysis. Over time, more complete data will be available. Then Indonesians will be able to conduct more complete and accurate analyses. <br />
<br />
<!--T:12--><br />
The course is delivered in Excel. Excel was chosen because it is cheap, available to most Indonesian staff and intuitive. Analyses in Excel will allow staff to make some useful conclusions about iSIKHNAS data. <br />
<br />
<!--T:13--><br />
If you intend to do a lot of important statistical work, you will need to learn how to use a complete statistical package instead of Excel. For this reason, we have also included some extension work for those participants who wish to extend their knowledge beyond Excel. This is presented in Appendix 1. Here R, a free online statistical package is introduced. R is one of the most useful software packages in the world. Better still it is free and downloadable from the internet. Appendix 1 repeats case study 1 in R.<br />
<br />
<!--T:14--><br />
Many screenshot videos will be used to assist you in understanding how to do exercises during the course. These can be played on several different software platforms including Windows media player.<br />
<br />
===[[Data Analysis Facilitator material]]=== <!--T:15--><br />
[[File:Nuvola apps edu miscellaneous.png|60px|left]]<br />
<br />
<br />
<br />
=== Overview of data analysis === <!--T:16--><br />
==== Relevance of data analysis to animal health policy ====<br />
In order to make good animal health policy, a veterinarian needs to understand the animal health situation where they work. For example, how much disease is present? Or, what is causing disease and how are various interventions working? <br />
<br />
<!--T:17--><br />
To gain this understanding a veterinarian could guess at the situation or they could make assumptions based on their own experience. These are generally poor means of making decisions. Decisions made by guessing are made in the absence of information. Decisions made on their own experience can be useful but are generally based on a very small amount of experience. That is, decisions are based on the experience of only one veterinarian, even if that veterinarian is very experienced. <br />
<br />
<!--T:18--><br />
A better means of decision making for veterinarians is to make decisions based on information that reflects the broader animal health situation. This information can be received in several ways, such as in animal health data, publications, text books and reports. Fortunately, animal health information (data) is now being collected across much of Indonesia. This data is recorded in iSIKHNAS. This data can assist good decision making if it is analysed and interpreted appropriately. The broad objective of this course is to assist you to do this. <br />
<br />
<!--T:19--><br />
Whilst you will learn a lot in the next several days, it is important that soon after completing this course you begin to download and analyse your own iSIKHNAS data. This will ensure that you consolidate your learning, improve your skills and at the same time improve your evidence based decision making. So please, set a day aside next week to do some of your own data analyses using the skills you learn here. Then regularly do some analysis of iSIKHNAS data. Over time your skills will improve. <br />
<br />
==== Introduction to the basic steps of data analysis ==== <!--T:20--><br />
There are several recognised steps to analyse and interpret data. These steps are determining an objective for your analyses, data management, describing data and testing hypotheses. Each of these will be briefly introduced here. Then the rest of the manual uses the four steps in the case studies. <br />
<br />
===== Objective ===== <!--T:21--><br />
It is important to have a clear and concise objective for your analysis. For example, what is the prevalence of diarrhoea in cattle for 2014? This then allows you to be focused in your efforts and to source appropriate data to address the objective. An objective is then translated into a hypothesis and tested. <br />
<br />
===== Data management ===== <!--T:22--><br />
It is important that veterinarians know how to access iSIKHNAS data and use it. We will help you to download iSIKHNAS data. We will also help you to preserve, error check, create and evaluate the iSIKHNAS data. <br />
<br />
===== Description of data ===== <!--T:23--><br />
The next step is to describe the data. One purpose of this step is to further check data for errors. Another purpose is to understand the structure and nature of data and the relationships between different parts of the data. In this step, single variable summaries, summaries of relationships between variables and plots are used. This helps you to start hypothesis testing (step 4).<br />
<br />
===== Hypothesis testing ===== <!--T:24--><br />
In order to comprehensively address an animal health question it is important to develop a testable question (or hypothesis) from your objective. This hypothesis can then be tested using appropriate statistical tests and you can decide whether the data supports your idea.<br />
<br />
<!--T:25--><br />
[[Data Analysis:Notes Sampling|'''Notes: Key concepts for Sampling''']]<br />
<br />
===Case Studies=== <!--T:26--><br />
<br />
<!--T:27--><br />
* [[Case Study 1|Case study 1: Performance measures for veterinary services]]<br />
* [[Case Study 2|Case study 2: Seasonal prevalence of diarrhoea (Mencret) in cattle]]<br />
* [[Case Study 3|Case study 3: Beef self-sufficiency (based on slaughter statistics)]]<br />
<br />
=== Concluding remarks === <!--T:28--><br />
Data analysis is critical to good animal health management and policy formation. Indonesia is fortunate to have an excellent and newly functional animal health information system, iSIKHNAS. However, it is no use having one of the world's best information systems if no-one uses the data. Hence, this course has focused on helping you to begin to use iSIKHNAs data. These approaches may help you to improve animal health decision making. <br />
<br />
<!--T:29--><br />
There are several standard steps to data analysis, including developing a research question of interest (objective), data management, description and hypothesis testing. All of these steps were used in this course. In order to consolidate your new skills it is recommended that you apply these steps to questions of interest to you immediately upon your return to your workplace. For example if you spend a day or two per month for the next several months you will consolidate your new skills. <br />
<br />
<!--T:30--><br />
We have only had time to use a fraction of the available statistical approaches (e.g. measures of association and a chi-squared test). You may choose to expand your knowledge beyond what we have learnt in this course. There are a number of useful text books that can assist you in developing your statistical skills. ''Veterinary Epidemiologic Research ''(Dohoo et al., 2009) is a useful text book that covers veterinary epidemiology and presents some statistics in this field. ''Statistics for Veterinary and Animal Science ''(Petrie and Watson, 2006) is a useful text book that applies statistics more generally to veterinary science. If you decide that you really want to learn both R and expand your statistical knowledge you should complete the appendix on R. ''Introductory Statistics with R ''(Dalgaard, 2008) is a very useful text book that introduces both statistics and R. If you start using R, then the statistical world will be at your figure tips!<br />
<br />
<!--T:31--><br />
{{fpblock|Appendix 1: Extension work using R.|Nuvola_apps_kig.png|This appendix introduces the reader to R. It is for those course participants who do a substantial amount of statistical analyses (or aim to) and wish to improve their capability beyond what Excel allows. There may not be time to complete this appendix during the course, but it can be completed later.<br />
<br />
<!--T:32--><br />
R is a statistical and graphics software environment. It is widely recognised and used throughout the world. R provides a very powerful and flexible environment in which to conduct simple or complex statistics or to produce publication ready graphics. It is also free, and constantly updated. It is widely supported by a range of scientists who are constantly contributing new packages that expand the capability of R.}}<br />
<br />
<!--T:33--><br />
{{fpblock|Appendix 2: Answers to Exercises|Themes256.png|This is where you will find the answers to the exercises in this Data Analysis course.}}<br />
<br />
<br />
=== References === <!--T:34--><br />
Dalgaard, P., 2008. Introductory Statistics with R. Springer.<br />
<br />
<!--T:35--><br />
Dohoo, I., Martin, W., Stryhn, H., 2009. Veterinary Epidemiologic Research. VER Charlottetown.<br />
<br />
<!--T:36--><br />
Petrie, A., Watson, P., 2006. Statistics for Veterinary and Animal Science. Wiley.<br />
<br />
<br />
<br />
<br />
<!--T:37--><br />
----<br />
<references/><br />
</translate></div>Angushttp://wiki.isikhnas.com/index.php?title=Epidemiological_Data_Analysis&diff=39102Epidemiological Data Analysis2015-11-28T08:22:14Z<p>Angus: </p>
<hr />
<div><languages/><br />
<translate><br />
==Data analysis using iSIKHNAS data case studies==<br />
[[File:Autoship1256.png|120px|left]]<br />
<br />
<br />
<br />
=== Pre-requisites ===<br />
This course is for veterinarians within the Indonesian animal health system. It is assumed that participants will have completed the ''Excel'', ''Basic Field Epidemiology'' and ''Surveillance'' training modules before this course. If you already know about epidemiology and how to use Excel, then these pre-requisite modules are not required.<br />
<br />
=== Objectives of course ===<br />
[[File:Target colour.jpg|60px|left]]<br />
<br />
The broader aim of the course is help participants make evidence based animal health policy decisions. This will assist them to improve livestock production and health in Indonesia. <br />
<br />
To do this, participants need to be able to access, understand and analyse information on animal health in Indonesia. Fortunately, a new initiative in Indonesia means that Indonesian animal health staff has access to one of the best animal health information systems in the world: iSIKHNAS. This provides staff with large amounts of high quality information (data<ref name="ftn1">The Oxford dictionary definition of data is: Facts and statistics collected together for reference or analysis</ref>) that they can use to make good animal health decisions. Therefore, the objectives of this course are to teach participants to download, understand, evaluate, analyse and interpret iSIKHNAS data. <br />
<br />
=== Learning approach ===<br />
[[File:Nuvola apps edu miscellaneous.png|60px|left]]<br />
<br />
This course will be taught by analysing real iSIKHNAS data. Three case studies will be presented. During each case study, a question will be asked. Then the question will be answered by participants during practical exercises. Spaces are included after each exercise where you can write your answers. Answers to exercises are provided as Appendix 2. It is generally recommended that you answer the question before reading the answers. <br />
<br />
Sometimes, notes on core concepts will be presented before or during case studies to support learning. These are backgrounded with grey to enable you to distinguish these notes from the exercises. <br />
<br />
The course is very applied and relevant to Indonesian animal health staff. The three case studies concentrate on: assessment of veterinary services (staff performance), disease management (diarrhoea in cattle) and livestock production (beef self-sufficiency). <br />
<br />
The data used in this training course was downloaded in early 2014. This was when iSIKHNAS had been operating for approximately a year in a small part of Indonesia. This early data was used so that we could provide answers to exercises. You may wish to download newer and more complete data to analyse during exercises at the time of your course. Please be aware that if you do, you will not have answers to check your work. <br />
<br />
The interim nature of the data means that no real conclusions can be made about the results of data-analyses conducted during this course. Instead, we conducted the analyses and made conclusions to demonstrate and teach data analysis. Over time, more complete data will be available. Then Indonesians will be able to conduct more complete and accurate analyses. <br />
<br />
The course is delivered in Excel. Excel was chosen because it is cheap, available to most Indonesian staff and intuitive. Analyses in Excel will allow staff to make some useful conclusions about iSIKHNAS data. <br />
<br />
If you intend to do a lot of important statistical work, you will need to learn how to use a complete statistical package instead of Excel. For this reason, we have also included some extension work for those participants who wish to extend their knowledge beyond Excel. This is presented in Appendix 1. Here R, a free online statistical package is introduced. R is one of the most useful software packages in the world. Better still it is free and downloadable from the internet. Appendix 1 repeats case study 1 in R.<br />
<br />
Many screenshot videos will be used to assist you in understanding how to do exercises during the course. These can be played on several different software platforms including Windows media player.<br />
<br />
===[[Data Analysis Facilitator material]]===<br />
[[File:Nuvola apps edu miscellaneous.png|60px|left]]<br />
<br />
<br />
<br />
=== Overview of data analysis ===<br />
==== Relevance of data analysis to animal health policy ====<br />
In order to make good animal health policy, a veterinarian needs to understand the animal health situation where they work. For example, how much disease is present? Or, what is causing disease and how are various interventions working? <br />
<br />
To gain this understanding a veterinarian could guess at the situation or they could make assumptions based on their own experience. These are generally poor means of making decisions. Decisions made by guessing are made in the absence of information. Decisions made on their own experience can be useful but are generally based on a very small amount of experience. That is, decisions are based on the experience of only one veterinarian, even if that veterinarian is very experienced. <br />
<br />
A better means of decision making for veterinarians is to make decisions based on information that reflects the broader animal health situation. This information can be received in several ways, such as in animal health data, publications, text books and reports. Fortunately, animal health information (data) is now being collected across much of Indonesia. This data is recorded in iSIKHNAS. This data can assist good decision making if it is analysed and interpreted appropriately. The broad objective of this course is to assist you to do this. <br />
<br />
Whilst you will learn a lot in the next several days, it is important that soon after completing this course you begin to download and analyse your own iSIKHNAS data. This will ensure that you consolidate your learning, improve your skills and at the same time improve your evidence based decision making. So please, set a day aside next week to do some of your own data analyses using the skills you learn here. Then regularly do some analysis of iSIKHNAS data. Over time your skills will improve. <br />
<br />
==== Introduction to the basic steps of data analysis ====<br />
There are several recognised steps to analyse and interpret data. These steps are determining an objective for your analyses, data management, describing data and testing hypotheses. Each of these will be briefly introduced here. Then the rest of the manual uses the four steps in the case studies. <br />
<br />
===== Objective =====<br />
It is important to have a clear and concise objective for your analysis. For example, what is the prevalence of diarrhoea in cattle for 2014? This then allows you to be focused in your efforts and to source appropriate data to address the objective. An objective is then translated into a hypothesis and tested. <br />
<br />
===== Data management =====<br />
It is important that veterinarians know how to access iSIKHNAS data and use it. We will help you to download iSIKHNAS data. We will also help you to preserve, error check, create and evaluate the iSIKHNAS data. <br />
<br />
===== Description of data =====<br />
The next step is to describe the data. One purpose of this step is to further check data for errors. Another purpose is to understand the structure and nature of data and the relationships between different parts of the data. In this step, single variable summaries, summaries of relationships between variables and plots are used. This helps you to start hypothesis testing (step 4).<br />
<br />
===== Hypothesis testing =====<br />
In order to comprehensively address an animal health question it is important to develop a testable question (or hypothesis) from your objective. This hypothesis can then be tested using appropriate statistical tests and you can decide whether the data supports your idea.<br />
<br />
[[Data Analysis:Notes Sampling|'''Notes: Key concepts for Sampling''']]<br />
<br />
===Case Studies===<br />
<br />
* [[Case Study 1|Case study 1: Performance measures for veterinary services]]<br />
* [[Case Study 2|Case study 2: Seasonal prevalence of diarrhoea (Mencret) in cattle]]<br />
* [[Case Study 3|Case study 3: Beef self-sufficiency (based on slaughter statistics)]]<br />
<br />
=== Concluding remarks ===<br />
Data analysis is critical to good animal health management and policy formation. Indonesia is fortunate to have an excellent and newly functional animal health information system, iSIKHNAS. However, it is no use having one of the world's best information systems if no-one uses the data. Hence, this course has focused on helping you to begin to use iSIKHNAs data. These approaches may help you to improve animal health decision making. <br />
<br />
There are several standard steps to data analysis, including developing a research question of interest (objective), data management, description and hypothesis testing. All of these steps were used in this course. In order to consolidate your new skills it is recommended that you apply these steps to questions of interest to you immediately upon your return to your workplace. For example if you spend a day or two per month for the next several months you will consolidate your new skills. <br />
<br />
We have only had time to use a fraction of the available statistical approaches (e.g. measures of association and a chi-squared test). You may choose to expand your knowledge beyond what we have learnt in this course. There are a number of useful text books that can assist you in developing your statistical skills. ''Veterinary Epidemiologic Research ''(Dohoo et al., 2009) is a useful text book that covers veterinary epidemiology and presents some statistics in this field. ''Statistics for Veterinary and Animal Science ''(Petrie and Watson, 2006) is a useful text book that applies statistics more generally to veterinary science. If you decide that you really want to learn both R and expand your statistical knowledge you should complete the appendix on R. ''Introductory Statistics with R ''(Dalgaard, 2008) is a very useful text book that introduces both statistics and R. If you start using R, then the statistical world will be at your figure tips!<br />
<br />
{{fpblock|Appendix 1: Extension work using R.|Nuvola_apps_kig.png|This appendix introduces the reader to R. It is for those course participants who do a substantial amount of statistical analyses (or aim to) and wish to improve their capability beyond what Excel allows. There may not be time to complete this appendix during the course, but it can be completed later.<br />
<br />
R is a statistical and graphics software environment. It is widely recognised and used throughout the world. R provides a very powerful and flexible environment in which to conduct simple or complex statistics or to produce publication ready graphics. It is also free, and constantly updated. It is widely supported by a range of scientists who are constantly contributing new packages that expand the capability of R.}}<br />
<br />
{{fpblock|Appendix 2: Answers to Exercises|Themes256.png|This is where you will find the answers to the exercises in this Data Analysis course.}}<br />
<br />
<br />
=== References ===<br />
Dalgaard, P., 2008. Introductory Statistics with R. Springer.<br />
<br />
Dohoo, I., Martin, W., Stryhn, H., 2009. Veterinary Epidemiologic Research. VER Charlottetown.<br />
<br />
Petrie, A., Watson, P., 2006. Statistics for Veterinary and Animal Science. Wiley.<br />
<br />
<br />
<br />
<br />
----<br />
<references/><br />
</translate></div>Angushttp://wiki.isikhnas.com/index.php?title=SMS_handler_setup&diff=39067SMS handler setup2015-07-08T10:10:52Z<p>Angus: </p>
<hr />
<div><languages/><br />
<translate><br />
= Overview = <!--T:1--><br />
An SMS handler is a function that controls the process of receiving and parsing data from an incoming SMS, checking the data, inserting it into a table and providing any response messages required. The creation of an SMS handler function is automated and can be achieved by providing metadata through the web interface. The process involves:<br />
* Setting up the general message information (format, premissions, purpose, data table, error message etc)<br />
* Setting up the details for each of the fields<br />
* Populating reference tables<br />
* Creating the data table<br />
* Creating message strings for outgoing messages<br />
These steps are described in detail below.<br />
<br />
= Message attributes = <!--T:2--><br />
The interface to edit message attributes is available through the Admin | Create SMS Handler | Edit SMS Message menu options. The fields are:<br />
== Start code ==<br />
Every message has a start code. This must contain only letters (no numbers, symbols, spaces or punctuation), and should be written in capital letters. It must be at least one letter, but can be longer. It is best to keep it as short as possible, while still allowing it to be easily understood and unique. Two or three letters is normal.<br />
== Name ==<br />
The name for the message is a short name describing the purpose of the message or the type of data being collected. It should be written in Indonesian and English.<br />
== Permission ==<br />
This controls who is allowed to send this type of message. The drop down list shows all defined group permissions, normally named in the form 'can_dosomething'. If there is an existing permission that is already suitable for this type of report, that can be used, but normally it will be necessary to define a new permission. Once defined, and associated with the SMS message, different user groups can be give this permission or not, depending on their responsibilities.<br />
=== Defining a new permission ===<br />
In the menu, go to Admin | Permissions | Edit Permissions. <br />
==== Name ====<br />
Enter a new name for the permission in the form 'can_xxx'. For a permission for a particular SMS message, the normal name for the permission is 'can_send_''message_type'''. For example, for an OB message, the corresponding permission would be 'can_send_ob'.<br />
==== Enable by default ====<br />
This sets all groups to have this permission by default. Normally this should be set to 'no' so that groups have to be explicitly give this permission, unless it is sure that almost all users should be able to use this permission.<br />
==== User permission ====<br />
Set this to 'no' as we are creating a group permission. <br />
<br />
Save the permission and return to Edit SMS Message, selecting the permission that you have created.<br />
== Purpose and Help Text == <!--T:3--><br />
These are currently not used but will be used in documentation and the interface in future. <br />
== Table name ==<br />
This is the name of an existing database table into which the received data will be inserted. Type the name of the table.<br />
<br />
Only the first table name is required. The second and third are used in special cases where data is distributed amongst several tables<br />
<br />
== Error message ==<br />
This is a key to a string which will be used as the error message if the general format of the message is incorrect. Normally it is in the form ''message_type''_error. For example, for an OB message, the name would be OB_error.<br />
== Reply SQL ==<br />
This is an SQL 'select' query that controls what message is returned to the sender. It must always be defined.<br />
<br />
<!--T:4--><br />
The SQL should return a single varchar value which is the text of the message that will be returned to the sender. At its very simplest, it could be something like: <br />
select 'Thank you. Your message has been received'<br />
<br />
<!--T:5--><br />
However, all reply messages should confirm the contents of the submitted message, converted from the coded version into clear text. The reply SQL is therefore normally more complex, and queries the newly inserted data (filtering by the message id), joins it to references tables, and composes the result. It also normally uses language-specific strings from the translation table to present the message in the correct form. <br />
<br />
<!--T:6--><br />
Pre-defined variables that can be included in the SQL (and almost always are) are:<br />
* sms_userid: the user ID of the person sending the message. This is used to get the right language.<br />
* sms_msgid: the message ID for the current message. This is used to get the submitted data.<br />
<br />
<!--T:7--><br />
Helpful functions that may be included in replay SQL include:<br />
* get_string(key varchar, userid integer): returns a defined string (indexed by the key) in the user's preferred language<br />
* get_user_lang(userid integer): return the language code for the user. This is useful if directly accessing data from a translated array field.<br />
* add_checkdigit(code integer): when returning a numeric code (case ID, program ID etc), a check digit is used to ensure that there are no typographical errors. This function adds a check digit to the raw code. All ID codes should have a check digit added, as if they are used in a message without the check digit, it will be interpreted as an error by the system. <br />
* format(format_string varchar, input_string varchar,...): This is a standard PostgreSQL function to format a string with a list of replaceable variables. The string should contain one or more %s place holders, which are replaced with the value of the variables specified.<br />
* string_agg(string varchar, separator varchar): another standard SQL function that aggregates string from multiple rows (when using a 'group by' clause) into a single concatenated value, with each row's string be separated by the separator. This is useful when the message might insert data into multiple rows, and the reply needs to summarise the data from these rows.<br />
<br />
<!--T:8--><br />
An example of a reply SQL for the OB message:<br />
select format(get_string('OB_reply',sms_userid), dinfo, s.species[1], l.name)<br />
from ( <br />
select t.caseid, string_agg(format('%s (%s %s)', d.name, dose, units), ', ') as dinfo <br />
from treatments t<br />
join drugs d on d.id = drug<br />
where t.msgid = sms_msgid group by t.caseid) as dd<br />
left join cadre_reports c on c.id = dd.caseid<br />
left join locations l on l.id = c.locationid<br />
left join species s on s.id = c. speciesid<br />
<br />
== Alert SQL == <!--T:9--><br />
The Alert SQL is used to send immediate SMS messages to users other than the original sender, alerting them of the contents of the original SQL or of other information. If no alert message is required, this field should be left blank.<br />
<br />
<!--T:10--><br />
This is a 'select' statement returning one or more records with two fields: the phone number (varchar, from the users.phone field), and the message content (varchar).<br />
<br />
<!--T:11--><br />
The same variables and functions described above are available for use in this message. An example of the Alert SQL for the Q message is:<br />
<br />
<!--T:12--><br />
select u2.phone, <br />
format(get_string('Q_alert',2), u.firstname||coalesce(' '||u.surname,''), <br />
local_phone(u.phone), to_char(report_date,'HH:MM:SS'), question)<br />
from questions q<br />
join users u on u.id = q.userid<br />
join users u2 on (not u2.del) and (u2.phone is not null) and (u2.groupid < 2)<br />
join locations l on l.id = u2.location<br />
join locations l2 on l2.id = u.location<br />
where q.msgid = sms_msgid<br />
<br />
== Protected == <!--T:13--><br />
Mark 'yes' to protect this message from being overwritten by the message creation process. Any message function that has had custom modifications made to its code should be marked as protected to avoid being overwritten by the automatic message generator function.<br />
<br />
= Field attributes = <!--T:14--><br />
Once the message attributes are defined, the fields for the message need to be defined. This is done from the menu: Admin | Create SMS Handler | Edit SMS Fields<br />
<br />
== Message == <!--T:15--><br />
Select the existing message defined in the previous step<br />
<br />
== Natorder == <!--T:16--><br />
Natural order. Type an integer to define the order of fields in the SMS. Each field must have a different sequential value.<br />
<br />
== Name == <!--T:17--><br />
Enter a name in English and Indonesian. This appears in documentation and is used internally. It may contains spaces. It should briefly describe what the content of the field is.<br />
<br />
== Data type == <!--T:18--><br />
The following data types are defined:<br />
<br />
===== Numeric code ===== <!--T:19--><br />
This is a number containing a check digit. Its main use is case ID, but it is used in a number of other situations where users need to send and receive numeric codes.<br />
<br />
===== Lookup code ===== <!--T:20--><br />
This is a alpha (letters only) code (one or more letters), which is used to look up a value from a reference table. This is the most common way to refer to reference table values.<br />
<br />
===== Integer ===== <!--T:21--><br />
This is a simple integer, used for counts in the data submitted (number of animals slaughtered, vaccinated, sick etc.)<br />
<br />
===== Location ===== <!--T:22--><br />
This is a location code, which can be a full version (8 digits in the new system, 10 in the old), or short (just the last digits below the users area of responsibility).<br />
<br />
===== Boolean ===== <!--T:23--><br />
A single letter text code that can take two values, defaulting to Y (Ya, yes), and T (tidak, no). SQL can be used to define other alternatives. <br />
<br />
===== Text ===== <!--T:24--><br />
Free text with any characters. This normally has to be the last field in a message as it is difficult to parse.<br />
<br />
===== Float ===== <!--T:25--><br />
A number that may contain a decimal point, for example, drug doses or coordinates.<br />
<br />
===== Integer code ===== <!--T:26--><br />
An integer used to lookup a value from a reference table. This is not commonly used (alpha codes are used instead).<br />
<br />
===== Text array ===== <!--T:27--><br />
A field containing one or more lookup codes (alpha codes referencing values in a table). These values are parsed and inserted into a single array field in the data table. In this way, multiple values can be handled as a single field type. This is used for signs and differential diagnoses, for example. Care is required to ensure that parsing is unambiguous (last field, or surrounded by numeric fields).<br />
<br />
===== Date ===== <br />
A field which allows the user to submit a date. Dates are submitted in one of the following formats:<br />
* dd/mm/yyyy<br />
* dd/mm/yy (assumes 21st century)<br />
* mm/yyyy (assumes 15th of the month)<br />
* mm/yy (assumes 15th of the month, 21st century)<br />
* dd.mm.yyyy and other variations above<br />
* dd-mm-yyyy and other variations above<br />
Dates are stored in date fields in the database.<br />
<br />
== Optional == <!--T:28--><br />
This indicates if the field is optional or not.<br />
<br />
== Group sequence == <!--T:29--><br />
SMS messages can contain repeating groups of fields. For example a POP population message can contain multiple pairs of ([species] [number]...). <br />
When a field is not part of a repeating group, it should have a group sequence of 0. If it is part of a group, then each element of the group should be numbered sequentially. Only one repeating group is permitted in a message.<br />
<br />
== Lookup SQL == <!--T:30--><br />
This is a select statement with a different purpose depending on the field type. When not required, it can be left blank. When used, it should contain a single %s value which is replaced with the value of the field. Return types vary with the field type.<br />
<br />
===== Lookup code ===== <!--T:31--><br />
The SQL returns the id from the reference table of the value submitted. The SQL is required in this case. For example:<br />
<br />
<!--T:32--><br />
select id from drugs where upper(code) = upper(trim(%s))<br />
<br />
===== Integer or Date ===== <!--T:33--><br />
The SQL is required. If provided it is used for range checking. It should return a single boolean value. For example:<br />
<br />
<!--T:34--><br />
select %s between 0 and 1000<br />
<br />
===== Text array ===== <!--T:35--><br />
The SQL is required. It returns an array of ID values for the codes in the input array. The requirements are rather special:<br />
* two %s parameters<br />
** First one: select %s from<br />
** Second one: (select unnest(regexp_matches(%s,'([a-z]+)', 'igx')) as code) as dat<br />
* join to main table: left outer join diseases s on upper(dat.code) = upper(s.code)<br />
** table '''must''' be aliased 's'<br />
* other join clauses and filters<br />
<br />
<!--T:36--><br />
For example:<br />
<br />
select %s from<br />
(select unnest(regexp_matches(%s,'([a-z]+)', 'igx')) as code) as dat<br />
left outer join diseases s on upper(dat.code) = upper(s.code)<br />
AND NOT del<br />
AND (valid_from IS NULL OR valid_from <= CURRENT_DATE)<br />
AND (valid_to IS NULL OR valid_to >= CURRENT_DATE)<br />
<br />
===== Boolean ===== <!--T:37--><br />
The SQL is optional. If present, it returns a boolean value for the submitted code. For example:<br />
select case upper(trim(%s)) <br />
when 'K' then true<br />
when 'Y' then true<br />
when 'T' then false <br />
when 'N' then false<br />
else null end<br />
<br />
== Field name == <!--T:38--><br />
The field in the database table into which the data received will be inserted.<br />
<br />
== Error message == <!--T:39--><br />
A key reference to an string in the translation table that will be used as the error message for this field. The key should contain one replaceable parameter (%s) which is replaced with the (invalid) value submitted.<br />
<br />
= Reference tables = <!--T:40--><br />
Reference tables are in the reference schema. Structure varies but most have at least the following fields:<br />
* id: unique record id<br />
* code: an alpha code<br />
* hier_code: a dot separated hierarchical code in the form 1.1.1. This is used to arrange data at different levels of detail, allowing more flexible analysis<br />
* name: varchar[] - a text array field with the name in Indonesian at index 1, and English at index 2<br />
* valid_from and valid_to: dates indicating the period of validity of the item. Valid_to may be null indicating ongoing validity.<br />
* modified_by: user id of the last user to modify the value<br />
* modified_on: timestamp of the last modification<br />
* del: boolean flag for deleted<br />
<br />
<!--T:41--><br />
In addition, there may be classifications referring to other tables (eg species) or flags (eg zoonosis, OIE etc for diseases)<br />
<br />
= Data tables = <!--T:42--><br />
Data tables are stored in the 'data' schema. Their structure depends on the data required, but they must have have the following fields which are automatically updated:<br />
* id: unique record id<br />
* userid: integer referencing the user ID of the submitting user (from the 'users' table);<br />
* report_date: timestamp of data submission<br />
* msgid bigint: the unique id of the incoming SMS message<br />
* created_on and modified_on: dates<br />
* created_by and modified_by: user IDs<br />
* del: deleted flag<br />
<br />
= Message strings = <!--T:43--><br />
Translated message strings are stored against a key in the translation table, and can be edited using the menu Admin | Message codes and translations | SMS messsage text. <br />
<br />
<!--T:44--><br />
The key or string code is used to access the message. By convention, this code starts with the message start code, followed by an underscore and then an abbreviation of the purpose. For example a message with an error due to an invalid drug code when sending a treatment (OB) message might be OB_invdrug.<br />
<br />
<!--T:45--><br />
The strings are stored in Indonesian and English (and this can be expanded to other languages if required). <br />
<br />
<!--T:46--><br />
Most messages have data inserted into them, so are used with the SQL '''format()''' function. For this to work, they need to have place holders for the data to insert, in the form %s. For example:<br />
<br />
<!--T:47--><br />
Laporan tindak lanjut dari %s (ID kasus %s) %s. %s<br />
<br />
<!--T:48--><br />
would have the following data substituted into it: village name, case ID, the numbers of animals and whether the outbreak is resolved or ongoing.<br />
<br />
= Building the message function = <!--T:49--><br />
Once the metadata, tables and strings for an SMS handler function have been set up, the function needs to be generated before it can be used. Use the menu Admin | Create SMS handler | Create handler function, and select the function to generate. Once generated, the function will be saved in the SMS schema, and be immediately available for use.<br />
<br />
= Testing the message function = <!--T:50--><br />
To test a new function, use the Instant Messaging system. This allows a message to be composed and submitted to the system as if it were being sent by SMS. The message is inserted into the inbox, normal processing follows, and any response messages are inserted into the outbox and returned to the sender via IM. Note that any data submitted is inserted into the database so be sure to delete any test data afterwards if using the live server<br />
<br />
<br />
</translate></div>Angushttp://wiki.isikhnas.com/index.php?title=Spreadsheet_data_submission_manual/id&diff=37536Spreadsheet data submission manual/id2015-05-12T06:03:40Z<p>Angus: </p>
<hr />
<div>[[Manual penggunaan form pengisian uji laboratorium iSIKHNAS|Versi bahasa Indonesia]]<br />
=Panduan pengiriman data lembar lajur=<br />
<br />
Panduan ini berisi petunjuk pengiriman data laboratorium melalui iSIKHNAS dengan menggunakan lembar lajur (spreadsheet) Excel. <br />
<br />
==Pengantar dan ikhtisar==<br />
Prosesnya secara keseluruhan cukup sederhana: <br />
*Buka pola acu (template) lembar lajur dan lembar lajur standar data yang tertaut. <br />
*Masukkan data laboratorium yang akan dikirim. <br />
*Kirimkan lembar lajur ke iSIKHNAS melalui surat elektronik (email).<br />
<br />
iSIKHNAS secara otomatis akan memeriksa data yang diterima dan, apabila tidak ada masalah, menambahkannya ke basis data (database) nasional. Setelahnya akan ada surat elektronik balasan berisi konfirmasi bahwa data telah terkirim dengan benar disertai laporan klien yang dihasilkan secara otomatis untuk dicetak di laboratorium.<br />
<br />
Untuk dapat menggunakan sistem tersebut, staf laboratorium membutuhkan hal-hal berikut ini: <br />
*Terdaftar pada iSIKHNAS (tanyakan kepada koordinator lokal). <br />
*Memiliki kewenangan untuk mengirimkan data laboratorium (tanyakan kepada koordinator lokal). <br />
*Unit komputer yang telah dilengkapi dengan: <br />
**Salinan lembar lajur pengiriman data. <br />
**Salinan lembar lajur standar laboratorium.<br />
<br />
Karena sistem ini bekerja berdasarkan Excel dan surat elektronik, maka anda juga membutuhkan hal-hal berikut ini: <br />
* Perangkat lunak Excel yang telah diinstalasi pada komputer anda (dengan versi yang dapat membuka dokumen dengan format '.xlsx'); dan <br />
* alamat surat elektronik dan koneksi internet untuk mengirim dan menerima surat elektronik. Untuk mengirim dan menerima surat elektronik, anda dapat menggunakan fasilitas berikut ini: <br />
** Antarmuka web-mail (misalnya Gmail) melalui perangkat lunak peramban (misalnya Chrome, Internet Explorer atau Firefox); atau <br />
** perangkat lunak surat elektronik (misalnya Microsoft Outlook atau Thunderbird).<br />
<br />
==Pengaturan==<br />
Untuk dapat menggunakan sistem ini, anda membutuhkan dua jenis lembar lajur berikut ini: <br />
# Pola acu (template) lembar lajur. <br />
# Lembar lajur 'lab standards.xlsx' - yang berisi standar data laboratorium nasional Indonesia untuk memastikan kompatibilitas data sehingga dapat dianalisis.<br />
<br />
Keduanya dapat diunduh dari situs web iSIKHNAS.<br />
<br />
====Pola acu lembar lajur untuk pengiriman data====<br />
[[image:labdatatemplate.png]]<br />
<br />
Lembar lajur ini digunakan untuk memasukkan data dan kemudian dikirimkan ke iSIKHNAS melalui surat elektronik.<br />
Klik tautan berikut ini untuk mengunduh versi terbaru dari lembar lajur pengiriman data:<br />
<br />
[[media:iSIKHNAS submission spreadsheet v5.8.xlsx|Submission spreadsheet]]<br />
<br />
Pola acu lembar lajur ini akan diperbarui dari waktu ke waktu. Koordinator iSIKHNAS anda dapat mengirimkan versi lembar lajur terbaru melalui surat elektronik, atau memberi tahu versi terbaru yang dapat diunduh dari situs web ini.<br />
<br />
===Lembar lajur standar laboratorium===<br />
[[image:labstandards.png]]<br />
<br />
Dokumen '''lab standards.xlsx''' telah ditautkan secara otomatis pada pola acu lembar lajur untuk memastikan bahwa semua data yang akan dikirim sudah sesuai dengan standar data nasional. Langkah ini dilakukan dan disesuaikan secara otomatis oleh iSIKHNAS untuk masing-masing laboratorium. Setelah dokumen dibuat dan diunduh, anda tidak perlu lagi melakukan penyuntingan. Apabila ada perubahan, maka dapat dilakukan secara daring (''online'') melalui situs web iSIKHNAS dan kemudian diunduh. <br />
<br />
Lembar lajur tersebut dapat diunduh secara aman dari situs web iSIKHNAS. Lakukan ''log in'' dan lihat:<br />
* Manage | Export Lab standards<br />
atau klik tautan berikut ini untuk langsung masuk ke halaman pengunduh (anda harus sudah ''log in'' sebelum tautan ini dapat bekerja)<br />
<br />
https://www.isikhnas.com/en/exportlabstandards<br />
<br />
[[image:exportstandards.png]]<br />
<br />
# Pilih 'Custom lab references'<br />
# Pilih laboratorium anda dari daftar yang muncul <br />
# Pilihan yang tersedia:<br />
## Klik 'Export'<br />
### Langkah ini akan mengirimkan salinan dokumen standar laboratorium ke alamat surat elektronik anda yang telah terdaftar; atau <br />
## Klik 'Export to lab contact'<br />
### Langkah ini akan mengirimkan salinan dokumen standar laboratorium ke narahubung (''contact person'') yang tercantum pada daftar laboratorium iSIKHNAS (tabel infrastruktur).<br />
<br />
===Petunjuk penting dalam pengelolaan lembar lajur===<br />
<br />
{{hlbox|Selalu simpan pola acu lembar lajur dan lembar lajur standar laboratorium dalam '''direktori yang sama'''}}<br />
<br />
Jika masing-masing lembar lajur ditempatkan pada direktori yang berbeda, maka tautan diantara keduanya tidak akan bekerja.<br />
<br />
{{hlbox|Lembar lajur standar laboratorium harus selalu memiliki nama yang sama: '''lab standards.xlsx'''.}}<br />
<br />
Penggunaan nama yang berbeda akan membuat dokumen tersebut tidak bekerja.<br />
<br />
Ketika mengunduh lembar lajur standar laboratorium dari internet, kadangkala komputer anda secara otomatis akan mengganti nama dokumen yang diunduh menjadi nama lain seperti '''lab standards(2).xlsx'''. Jika ini terjadi, anda perlu menghapus salinan dokumen lama terlebih dahulu kemudian mengganti nama dokumen baru menjadi '''lab standards.xlsx''' dan menempatkannya pada direktori yang benar.<br />
<br />
{{hlbox|Anda dapat menyalin dan mengganti nama dokumen pola acu sesuai keinginan anda (tetapi tidak untuk dokumen standar laboratorium)}}<br />
<br />
Jika anda ingin menyimpan salinan dari setiap pengiriman yang pernah dilakukan, maka menamai masing-masing dokumen dengan menyertakan nomor ''epi'' dapat menjadi ide yang baik sehingga setiap dokumen dapat terlacak. Dokumen-dokumen tersebut dapat disimpan dalam direktori yang sama, selama dokumen '''lab standards.xlsx''' juga berada pada lokasi yang sama.<br />
<br />
==Pemasukkan data==<br />
Lakukan langkah berikut ini untuk memasukkan data ke dalam pola acu lembar lajur:<br />
# Buka lembar lajur '''lab standards.xlsx'''. <br />
# Buka pola acu lembar lajur.<br />
<br />
{{hlbox|Kedua lembar lajur harus dibuka pada waktu yang sama sehingga tautan diantara kedua dokumen tersebut dapat bekerja}}<br />
<br />
Masukkan data pada sel-sel yang sesuai dengan mengklik sel dan mengetikkan data yang diinginkan, atau mengklik tanda panah untuk memilih dari daftar yang muncul.<br />
<br />
====Pengendalian sel====<br />
Lembar lajur ini telah diatur sedemikian rupa untuk mencegah penambahan data pada tempat yang salah. Anda hanya dapat memilih sel-sel tertentu yang ditujukan untuk menyimpan data.<br />
<br />
=====Daftar pilihan=====<br />
[[image:dropdownlist.png]]<br />
<br />
Daftar pilihan berisi banyak sel. Hal ini dilakukan untuk memastikan agar data yang akan dikirim telah sesuai dengan standar data laboratorium nasional. Anda hanya dapat memilih salah satu nilai dari daftar pilihan.<br />
<br />
=====Nilai yang harus diisi=====<br />
[[image:requiredcell.png]]<br />
<br />
Apabila ada nilai kosong yang harus diisi, sel yang bersangkutan akan ditandai dengan garis tepi berwarna merah.<br />
<br />
===Petunjuk===<br />
[[image:hintmarker.png]]<br />
<br />
Banyak sel telah dilengkapi dengan petunjuk untuk memandu anda. Sel-sel ini ditandai dengan segitiga kecil di salah satu sudutnya.<br />
<br />
[[image:hint.png]]<br />
<br />
Untuk melihat petunjuk, gerakkan kursor tetikus anda di atas tanda segitiga kecil pada sudut sel untuk memunculkan teks yang dimaksud.<br />
<br />
==Temuan, hasil, diagnosis==<br />
Dalam iSIKHNAS, masing-masing istilah ini memiliki arti tersendiri.<br />
<br />
=====Temuan=====<br />
Ini merupakan hasil dari pengujian laboratorium. Temuan dapat berbentuk: <br />
* Kualitatif (misalnya terdeteksinya Coliform pada sampel); atau <br />
* kuantitatif (misalnya uji HI menunjukkan titer 1/40)<br />
Beberapa jenis pengujian dapat menghasilkan temuan kualitatif dan kuantitatif (misalnya sampel feses mengandung 300 telur ''Strongyloides'' per gram).<br />
<br />
=====Hasil=====<br />
Ini merupakan ''interpretasi'' dari temuan yang diperoleh. Biasanya hasil dapat berupa positif atau negatif. Sebagai contoh, temuan dari uji antibodi ELISA dapat berupa densitas optik sebesar 200. Jika kita menerapkan ambang batas 150, maka ini berarti interpretasi terhadap temuan tersebut akan menunjukkan hasil positif - hewan yang bersangkutan memiliki antibodi terhadap patogen tertentu. Hasil-hasil lain yang mungkin diperoleh antara lain ''protektif'' atau ''non-protektif'' ketika melakukan surveilans paska-vaksinasi; ''dalam batas aman'' atau ''di luar batas aman'' (uji keamanan pangan); kandungan ringan, medium atau berat (telur cacing).<br />
<br />
=====Diagnosis=====<br />
Ini merupakan kesimpulan yang diambil berdasarkan semua informasi yang tersedia mengenai penyakit apa yang menjadi masalah. Sebuah diagnosis hanya akan berarti jika terdapat suatu penyakit dan tujuan dari pengiriman data adalah untuk tujuan diagnostik. Beberapa poin kunci dalam hal ini antara lain:<br />
* Tidak ada diagnosis untuk surveilans, lalu lintas atau tujuan lainnya karena tidak adanya penyakit (yang diketahui).<br />
* AI negatif ''bukan'' merupakan sebuah diagnosis. Ini merupakan hasil (interpretasi informasi yang diperoleh dari pengujian) dan tidak dapat memberi tahu kita penyakit apa yang menjadi masalah.<br />
<br />
==Pedoman masing-masing kolom==<br />
====Pengajuan uji laboratorium====<br />
Informasi mengenai pengiriman data.<br />
<br />
=====Nomor Epi=====<br />
Harus diisi. Nomor pengiriman unik yang diberikan oleh laboratorium yang bersangkutan.<br />
<br />
Pengiriman sampel dari satu laboratorium ke laboratorium yang lain harus selalu menggunakan nomor epi semula (jangan membuat nomor baru di laboratorium referensi).<br />
<br />
=====Tujuan=====<br />
Harus diisi. Tujuan pengiriman spesimen.<br />
<br />
=====ID kejadian iSIKHNAS=====<br />
Harus diisi untuk beberapa alasan. Ini merupakan nomor referensi iSIKHNAS untuk mengaitkan data laboratorium dengan data lainnya dalam iSIKHNAS.<br />
<br />
Kolom ini perlu diisi dengan:<br />
* Kasus diagnostik: ID kasus iSIKHNAS<br />
* Ijin lalu lintas: ID SKKH iSIKHNAS <br />
* Surveilans: ID program surveilans iSIKHNAS <br />
* Pemantauan paska-vaksinasi: ID program vaksinasi iSIKHNAS<br />
<br />
Selama iSIKHNAS masih dalam proses penerapan, tidak semua kabupaten/kota telah dapat menggunakan penomoran tersebut sehingga akan ada pengiriman yang tidak dilengkapi dengan ID iSIKHNAS walaupun seharusnya disertakan. Dalam hal ini, kolom tersebut dapat dibiarkan kosong.<br />
<br />
====Pemilik dan pengirim====<br />
Informasi mengenai lokasi, pengirim, dan pemilik. Lokasi harus selalu merupakan tempat di mana hewan yang bersangkutan berada.<br />
<br />
=====Lokasi (PKKD)=====<br />
Harus diisi. Pilih lokasi dari keempat daftar pilihan yang ada.<br />
<br />
Apabila terdapat perubahan nama lokasi karena perubahan batas wilayah administratif, cobalah untuk mencari nama lokasi tersebut sebelumnya.<br />
<br />
Jika lokasi yang terperinci tidak diketahui, masukkan sebanyak mungkin informasi yang tersedia (paling sedikit kabupaten dan provinsi).<br />
<br />
=====Kode lokasi=====<br />
Kolom ini otomatis terisi berdasarkan informasi di atas. Anda tidak dapat menyunting bagian ini<br />
<br />
=====Jenis Pengirim=====<br />
Harus diisi. Pilih dari daftar pilihan yang tersedia.<br />
<br />
=====Nama Pengirim=====<br />
Opsional. Informasi ini dicantumkan pada laporan klien.<br />
<br />
=====Alamat Pengirim=====<br />
Opsional. Informasi ini dicantumkan pada laporan klien.<br />
<br />
=====Nomor HP Pengirim=====<br />
Opsional. Sertakan nomor seluler jika tersedia. Data ini digunakan untuk mengidentifikasi pengirim sehingga dapat mengaitkan semua pengiriman dari sumber yang sama untuk keperluan konsolidasi pelaporan.<br />
<br />
=====Nama Pemilik=====<br />
Opsional. Informasi ini dicantumkan pada laporan klien.<br />
<br />
=====Alamat Pemilik=====<br />
Opsional. Informasi ini dicantumkan pada laporan klien.<br />
<br />
=====Nomor HP Pemilik=====<br />
Opsional. Sertakan nomor seluler jika tersedia. Data ini dapat mengaitkan pengiriman yang berbeda-beda dari sumber yang sama.<br />
<br />
====Spesimen dan uji====<br />
Informasi mengenai spesimen dan pengujian yang diperlukan. Setiap spesimen dan kombinasi pengujian yang berbeda dicantumkan pada kolom yang berbeda pula.<br />
<br />
[[image:multitests.png]]<br />
<br />
Apabila terdapat lebih dari satu temuan kualitatif untuk suatu pengujian tertentu (lihat di bawah), temuan-temuan tersebut dicantumkan pada kolom baru dengan perincian lain dibiarkan kosong.<br />
<br />
=====Kelompok spesimen and Jenis spesimen=====<br />
Harus diisi. Gunakan kedua kolom ini untuk memilih jenis spesimen (jenisnya atau bagian tubuh hewan yang menjadi asalnya).<br />
<br />
=====Bentuk spesimen=====<br />
Harus diisi. Informasi ini mengindikasikan bagaimana spesimen ditangani, disiapkan atau diperlakukan. Ini dapat mencakup cara pengambilan (''swab''), persiapan (''smear'') atau pengawetan (formalin).<br />
<br />
=====Jenis Uji=====<br />
Harus diisi. Informasi ini menentukan bagian laboratorium yang akan melaksanakan pengujian. Pengujian yang dicantumkan dalam daftar pilihan berikutnya bergantung pada daftar pengujian yang dimiliki masing-masing laboratorium dan bagian-bagiannya (lihat di bawah).<br />
<br />
=====Uji=====<br />
Harus diisi. Pengujian yang dilakukan.<br />
<br />
=====Temuan kual.=====<br />
Temuan kualitatif dari pengujian. Jika suatu pengujian menghasilkan satu atau lebih temuan kualitatif (misalnya terdeteksinya spesies bakteri atau parasit, atau temuan histopatologis), masing-masing temuan dicantumkan pada kolom yang berbeda di baris 29. Dengan cara ini, suatu pengujian dapat memiliki lebih dari satu temuan yang dicantumkan pada kolom yang berbeda.<br />
<br />
[[image:qualfindings.png]]<br />
<br />
====Perincian hewan====<br />
Pada bagian akhir pola acu lembar lajur terdapat informasi mengenai masing-masing hewan. Setiap baris berisi satu ekor hewan dan masing-masing hewan harus memiliki data hasil untuk setiap pengujian.<br />
<br />
=====Jenis kelamin=====<br />
Opsional. Masukkan jenis kelamin masing-masing hewan, jika diketahui.<br />
<br />
=====Umur and Unit Umur=====<br />
Opsional. Masukkan umur masing-masing hewan jika diketahui. Bagian umur dibagi menjadi dua kolom. Kolom pertama (Umur) hanya berisi angka (bilangan bulat atau desimal). Kolom kedua berisi unit waktu (hari, minggu, bulan atau tahun) yang dapat dipilih dari daftar pilihan yang tersedia. Unit waktu yang berbeda tidak dapat digunakan bersama-sama; jika seekor hewan berumur 2 tahun dan 3 bulan, maka masukkan 2,25 tahun.<br />
<br />
Anda tidak dapat menggunakan simbol-simbol lain seperti > 3. Gunakan perkiraan terbaik anda jika umur pasti tidak diketahui.<br />
<br />
=====Spesies=====<br />
Harus diisi. Pilih dari daftar yang tersedia.<br />
<br />
=====Ras=====<br />
Opsional. Beberapa spesies memiliki jumlah ras yang berbeda-beda. Tambahkan informasi ini jika diketahui. Kadangkala terdapat pilihan yang berbeda - misalnya sapi dapat diidentifikasi sebagai sapi potong atau perah, atau diklasifikasi berdasarkan rasnya (limousin, friesian). Gunakan informasi paling terperinci yang tersedia.<br />
<br />
=====ID hewan=====<br />
Harus diisi. Apabila hewan individual telah ditandai secara unik (misalnya dengan penanda telinga), maka gunakanlah penanda tersebut. Jika informasi tersebut tidak tersedia, maka anda dapat memberikan nomor urut pada masing-masing hewan yang dimulai dengan angka 1. <br />
<br />
Apabila hewan-hewan berada dalam kelompok campuran, maka anda dapat menambahkan informasi lain pada kolom ini. Contohnya jika hewan-hewan tersebut berasal dari pemilik yang berbeda, maka anda dapat mengidentifikasi masing-masing hewan dengan menggunakan nama pemilik dan nomor urut hewan.<br />
<br />
=====Temuan kuant.=====<br />
Temuan kuantitatif. Informasi ini diperlukan untuk pengujian yang menghasilkan keluaran kuantitatif. Harus diisi dengan bilangan bulat atau angka desimal.<br />
<br />
Saat ini tengah direncanakan untuk memungkinkan penggunaan "simbol ketidakpastian" seperti > (lebih besar dari), < (lebih kecil dari), atau ~ (nilai perkiraan); namun fitur ini belum diterapkan.<br />
<br />
=====Hasil=====<br />
Harus diisi. Pilih dari daftar yang tersedia.<br />
<br />
==Pengiriman data==<br />
===Penyimpanan dan pengiriman data===<br />
# Setelah pemasukkan data selesai, simpan pola acu lembar lajur pada komputer anda. Mungkin anda juga ingin mengubah nama dokumennya dengan menambahkan nomor Epi sehingga memudahkan pencarian kembali. <br />
# Buat surat elektronik baru.<br />
# Tambahkan alamat tujuan '''labdata@isikhnas.com'''.<br />
# Cantumkan nomor Epi pada kolom subyek (langkah ini opsional tetapi dapat membantu anda menentukan data apa saja yang sudah dikirim dengan hanya melihat folder 'sent mail').<br />
# Lampirkan pola acu lembar lajur yang sudah anda simpan.<br />
# Kirim surat elektronik tersebut.<br />
<br />
Apabila anda memiliki perangkat lunak surat elektronik yang telah diinstalasi secara lokal pada komputer anda (misalnya Thunderbird atau Outlook), pengiriman surat elektronik dapat menjadi lebih mudah dan cepat:<br />
# Dalam perangkat lunak Excel, buka menu File kemudian pilih '''Save and send'''; klik tombol '''Send as attachment'''. Langkah ini secara otomatis membuat surat elektronik baru dengan dokumen yang telah dilampirkan. <br />
# Masukkan alamat '''labdata@isikhnas.com''' dan kirimkan.<br />
<br />
===Respon dari iSIKHNAS===<br />
Untuk setiap pengiriman data ke iSIKHNAS, terdapat pesan jawaban otomatis yang seharusnya diterima dalam satu atau dua menit setelah pengiriman. Isi dari pesan jawaban tersebut bergantung pada data yang dikirimkan:<br />
<br />
====Pengiriman berhasil - laporan klien====<br />
Apabila semua data yang dikirimkan sudah benar, maka secara otomatis akan dimasukkan ke dalam iSIKHNAS. <br />
<br />
Kemudian anda akan menerima surat elektronik yang mengkonfirmasikan bahwa data telah diterima dan disertai dengan ringkasan data yang dikirim.<br />
<br />
Anda juga akan menerima surat elektronik kedua berisi laporan klien yang dibuat secara otomatis. Dokumen ini memiliki format ODT yang dapat dibuka dan disunting dengan [https://www.libreoffice.org Libre Office Writer] (gratis) atau Microsoft Word.<br />
<br />
[[image:clientreport.png]]<br />
<br />
Setelah membuka dokumen, anda dapat menambah lebih banyak informasi serta menyimpan maupun mencetaknya.<br />
<br />
====Terdapat kesalahan pada data====<br />
Apabila terdapat kesalahan pada data yang dikirim, anda akan menerima surat elektronik berisi daftar kesalahan yang terdeteksi beserta referensi selnya. <br />
<br />
[[image:errorhighlight.png]]<br />
<br />
Surat elektronik ini juga dilampiri salinan lembar lajur yang dikirimkan semula. Pada lembar lajur ini, sel-sel yang mengandung kesalahan akan ditandai dengan warna kuning dan disertai dengan tampilan komentar yang menjelaskan kesalahan tersebut.<br />
<br />
Apabila ini memang kesalahan, anda dapat memperbaikinya pada lembar lajur semula dan mengirimkannya kembali dalam surat elektronik yang baru.<br />
<br />
====Kesalahan sistem====<br />
Apabila terjadi kesalahan pada sistem, anda dapat menerima surat elektronik yang memberitahukan adanya kesalahan tersebut dan menginstruksikan anda untuk melaporkannya kepada koordinator. <br />
<br />
Teruskan surat elektronik tersebut kepada koordinator iSIKHNAS anda atau salah satu ''champion'' iSIKHNAS yang dapat membantu memecahkan masalah tersebut.<br />
<br />
==Menentukan perincian pengujian di laboratorium anda==<br />
Daftar bagian-bagian laboratorium, dan pengujian yang dapat dilakukan oleh setiap bagian, perlu disesuaikan untuk masing-masing laboratorium.<br />
<br />
Untuk membuat daftar pengujian, ''log in'' ke situs web iSIKHNAS dan masuk ke Manage | Laboratory Tests.<br />
<br />
[[image:managelabtests.png]]<br />
<br />
# Pilih pengujian dari daftar yang tersedia. Semua pengujian ini merupakan standar nasional; apabila terdapat pengujian yang tidak tercantum, maka anda harus menghubungi ''champion'' iSIKHNAS untuk memperbarui standar yang digunakan.<br />
# Pilih bagian laboratorium yang melakukan pengujian.<br />
# Pilih laboratorium anda dari daftar yang tersedia.<br />
# Tandai kotak yang sesuai apabila pengujian menghasilkan keluaran kualitatif. Sebagai contoh, identifikasi bakteri atau parasit akan menghasilkan temuan kualitatif - nama-nama bakteri atau parasit, sedangkan ELISA AI tidak - karena hanya melakukan pengujian untuk mendeteksi AI. <br />
# Tandai kotak yang sesuai apabila pengujian menghasilkan keluaran kuantitatif. Sebagai contoh, uji ELISA menghasilkan densitas optik berupa suatu bilangan (kuantitatif); penghitungan telur cacing pada feses juga menghasilkan suatu angka. Sebaliknya, Rose Bengal Test hanya menunjukkan hasil positif atau negatif yang bukan merupakan temuan kuantitatif. <br />
# Apabila dihasilkan temuan kuantitatif, pilih unit yang sesuai pada daftar yang tersedia. <br />
# Tandai kotak yang sesuai apabila laboratorium anda telah mendapatkan akreditasi resmi untuk melakukan pengujian tersebut.<br />
# Masukkan referensi metode khusus yang digunakan dalam pengujian tersebut (untuk dicantumkan pada laporan klien).<br />
<br />
==Memperbarui standar data==<br />
Standar laboratorium nasional dikelola secara terpusat untuk memastikan konsistensi dan kemampuan untuk menganalisis data secara otomatis. iSIKHNAS berupaya menerapkan standar ini, sehingga tidak memungkinkan pengiriman data yang tidak mengikuti standar tersebut.<br />
<br />
Standar ini mencakup seluruh aspek data yang dikelola, termasuk:<br />
* Spesies<br />
* Pengujian<br />
* Temuan<br />
* Jenis kelamin dan umur hewan<br />
* Spesimen<br />
<br />
Semua standar ini tercantum dalam lembar lajur '''lab standards.xlsx''' dan dapat dipilih dari daftar pilihan yang tersedia pada pola acu pengiriman data. <br />
<br />
Apabila anda menemukan nilai yang tidak tercantum dalam daftar standar, maka nilai tersebut dapat ditambahkan. Untuk memastikan konsistensi, proses ini dikelola oleh ''champion'' iSIKHNAS. <br />
<br />
Silakan menghubungi ''champion'' iSIKHNAS untuk mengajukan penambahan nilai baru ke dalam standar yang digunakan.</div>Angushttp://wiki.isikhnas.com/index.php?title=Translations:Spreadsheet_data_submission_manual/10/id&diff=37535Translations:Spreadsheet data submission manual/10/id2015-05-12T06:03:39Z<p>Angus: </p>
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<div>[[media:iSIKHNAS submission spreadsheet v5.8.xlsx|Submission spreadsheet]]</div>Angushttp://wiki.isikhnas.com/index.php?title=File:ISIKHNAS_submission_spreadsheet_v5.8.xlsx&diff=37534File:ISIKHNAS submission spreadsheet v5.8.xlsx2015-05-12T06:01:35Z<p>Angus: </p>
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<div></div>Angushttp://wiki.isikhnas.com/index.php?title=Spreadsheet_data_submission_manual&diff=37533Spreadsheet data submission manual2015-05-12T06:01:04Z<p>Angus: </p>
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<div><languages/><br />
<translate><br />
=Manual for spreadsheet data submission= <!--T:1--><br />
This manual provides guidance for the submission of laboratory data to iSIKHNAS using and Excel spreadsheet. <br />
<br />
==Introduction and overview== <!--T:2--><br />
The overall process is simple:<br />
* Open the spreadsheet template (and the linked data standards spreadsheet)<br />
* Enter the lab submission data <br />
* Send the spreadsheet by email to iSIKHNAS<br />
<br />
<!--T:3--><br />
iSIKHNAS automatically checks the data and, if it is valid, inserts it into the national database. An email is sent with confirmation that the data has been correctly submitted, as well as an automatically generated client report for printing in the lab.<br />
<br />
<!--T:4--><br />
To use the system, laboratory staff must:<br />
* register with iSIKHNAS (talk to your local coordinator)<br />
* have permissions set to be allowed to submit laboratory data (again, talk to your coordinator)<br />
* set up their computer<br />
** get a copy of the submission template<br />
** get a copy of the lab standards spreadsheet<br />
<br />
<!--T:5--><br />
As the system works with Excel and email, you naturally must have <br />
* a recent copy of Excel installed on your computer (one that can handle the newer '.xlsx' file formats), and<br />
* an email address and internet connection to send and receive emails. To send and receive emails you can use <br />
** a web-mail interface (like gmail) through a web browser (like Chrome, Internet Explorer or Firefox), or<br />
** an email client (like Microsoft Outlook or Thunderbird)<br />
<br />
==Setting up== <!--T:6--><br />
To be able to use the system you must have two spreadsheets:<br />
# the template<br />
# 'lab standards.xlsx' - which contains the Indonesian national laboratory data standards to ensure that all data is compatible and able to be analysed.<br />
<br />
<!--T:7--><br />
Both can be downloaded from the iSIKHNAS web site<br />
<br />
====Data submission template spreadsheet==== <!--T:8--><br />
[[image:labdatatemplate.png]]<br />
<br />
<!--T:9--><br />
This is used to enter the data, and is sent by email to iSIKHNAS.<br />
Click on the link below to download the latest version of the data submission spreadsheet:<br />
<br />
<!--T:10--><br />
[[media:ISIKHNAS submission spreadsheet v5.8.xlsx|Submission spreadsheet]]<br />
<br />
<!--T:11--><br />
The template may be updated from time to time. Your iSIKHNAS coordinator will either send you the updated spreadsheet by email, or let you know that a new version is available on this web site for download.<br />
<br />
===Laboratory standards spreadsheet=== <!--T:12--><br />
[[image:labstandards.png]]<br />
<br />
<!--T:13--><br />
The '''lab standards.xlsx''' file is automatically linked to the template, to ensure that all data submitted conforms to the national data standards. This is automatically customised for each different lab, and is generated by iSIKHNAS. Once it is generated and downloaded, you never need to edit it. If changes are required, they can be made on-line on the iSIKHNAS web site, and a new version downloaded. <br />
<br />
<!--T:14--><br />
The spreadsheet can be downloaded from the iSIKHNAS secure web site. Log in and go to:<br />
* Manage | Export Lab standards<br />
or click on the following link to go straight to the download page (you must already be logged in for this link to work)<br />
<br />
<!--T:15--><br />
https://www.isikhnas.com/en/exportlabstandards<br />
<br />
<!--T:16--><br />
[[image:exportstandards.png]]<br />
<br />
<!--T:17--><br />
# Select 'Custom lab references'<br />
# Select your lab from the drop down list<br />
# Either<br />
## Click on 'Export'<br />
### This will send a copy of the standards to your registered email address, or<br />
## Click on 'Export to lab contact'<br />
### This will send a copy to the lab contact person, as recorded in the iSIKHNAS list of laboratories (infrastructure table).<br />
<br />
===Important tips for spreadsheet management=== <!--T:18--><br />
<br />
<!--T:19--><br />
{{hlbox|Always save the template spreadsheet and the standards spreadsheet in the '''same directory'''}}<br />
<br />
<!--T:20--><br />
If they are in different directories, the automatic links will not work.<br />
<br />
<!--T:21--><br />
{{hlbox|The standards spreadsheet must always have the same name: '''lab standards.xlsx'''.}}<br />
<br />
<!--T:22--><br />
If the name is changed, it will not work.<br />
<br />
<!--T:23--><br />
When you download the standards spreadsheet from the web, sometimes your computer will automatically change the name to something like '''lab standards(2).xlsx'''. If this happens, you need to delete the old copy, and rename the file back to '''lab standards.xlsx''' as well as placing it in the correct directory.<br />
<br />
<!--T:24--><br />
{{hlbox|You can copy and rename the template file as many times as you like (but not the standards file)}}<br />
<br />
<!--T:25--><br />
You may want to keep a copy of every submission you send, so saving each file with the epi number is a good way to keep track of the files. They can all be in the same directory, as long as the '''lab standards.xlsx''' file is in the same directory.<br />
<br />
==Entering data== <!--T:26--><br />
To enter data into the template spreadsheet:<br />
# Open the '''lab standards.xlsx''' spreadsheet<br />
# Open the template spreadsheet<br />
<br />
<!--T:27--><br />
{{hlbox|Both spreadsheets must be open at the same time so that template can successfully link to the standards spreadsheet}}<br />
<br />
<!--T:28--><br />
Enter data into the required cells by clicking on the cell and typing, or clicking on the arrow to select from the drop-down list.<br />
<br />
====Controlled cells==== <!--T:29--><br />
The spreadsheet is protected to avoid entering data in the wrong places. You can only select cells intended for data entry<br />
<br />
=====Drop down lists===== <!--T:30--><br />
[[image:dropdownlist.png]]<br />
<br />
<!--T:31--><br />
There are many cells with drop down lists. These ensure that data follows the national laboratory data standards. You can only choose one of the values from the list<br />
<br />
=====Required values===== <!--T:32--><br />
[[image:requiredcell.png]]<br />
<br />
<!--T:33--><br />
When a value is required but missing, the cell is highlighted with a red border.<br />
<br />
===Hints=== <!--T:34--><br />
[[image:hintmarker.png]]<br />
<br />
<!--T:35--><br />
Many cells contain hints to guide you. These are marked with a small triangle in the corner of the cell.<br />
<br />
<!--T:36--><br />
[[image:hint.png]]<br />
<br />
<!--T:37--><br />
To view the hint, float your mouse over the triangle and the text will pop up.<br />
<br />
==Findings, results, diagnosis== <!--T:38--><br />
In iSIKHNAS each of these has a special meaning.<br />
<br />
=====Findings===== <!--T:39--><br />
This is what the lab test tells you. Findings can be <br />
* qualitative (for example, Coliforms were detected in a sample ) or <br />
* quantitative (an HI test gave a titre of 1/40)<br />
Some tests may give both qualitative and quantitative findings (for example a faecal sample contained 300 Strongyloides eggs per gram)<br />
<br />
=====Result===== <!--T:40--><br />
This is our ''interpretation'' of what the findings mean. Normally the result is either positive or negative. For example, the finding for an antibody ELISA may be an optical density of 200. If we use a cut-off of 150, this means that our interpretation of the finding is that the animal is positive - it has antibodies to the pathogen. Other possible results include ''protective'' or ''non-protective'' when doing post-vaccination surveillance; ''within acceptable limits'' or ''outside acceptable limits'' (food safety testing); light, medium or heavy load (worm eggs).<br />
<br />
=====Diagnosis===== <!--T:41--><br />
This is our conclusion, based on all the available information, as to what disease is causing the problem. A diagnosis is only meaningful when disease is present and the purpose of the submission is diagnostic. Some key points:<br />
* For surveillance, movement or other purposes, there is no diagnosis as there is no (known) disease<br />
* AI negative is ''not'' a diagnosis. It is a result (our interpretation of the information that the test gave). It does not tell us what disease is causing the problem.<br />
<br />
==Guidelines for specific fields== <!--T:42--><br />
====Pengajuan uji laboratorium====<br />
Information about the submission.<br />
<br />
=====Nomor Epi===== <!--T:43--><br />
Required. A unique submission number assigned by the laboratory.<br />
<br />
<!--T:44--><br />
When samples are sent from one laboratory to another, the original epi number should always be used (do not create a new one in the referral lab).<br />
<br />
=====Tujuan===== <!--T:45--><br />
Required. The reason for submission of the specimen.<br />
<br />
=====ID kejadian iSIKHNAS===== <!--T:46--><br />
Required for some reasons. This is the iSIKHNAS reference number, to link laboratory data to other data in iSIKHNAS.<br />
<br />
<!--T:47--><br />
This is should be used for:<br />
* Diagnostic cases: The iSIKHNAS case ID<br />
* Movement permits: The iSIKHNAS SKKH ID<br />
* Surveillance: The iSIKHNAS surveillance program ID<br />
* Post vaccination monitoring: The iSIKHNAS vaccination program ID<br />
<br />
<!--T:48--><br />
While iSIKHNAS is being rolled out, not all kabupaten will be using it, so some submissions will not have an iSIKHNAS ID even if they are meant to. In this case, leave the field empty<br />
<br />
====Pemilik dan pengirim==== <!--T:49--><br />
Information about the location, submitter and owner. The location should always be the location of the animal.<br />
<br />
=====Lokasi (PKKD)===== <!--T:50--><br />
Required. Select the location from the four drop down lists.<br />
<br />
<!--T:51--><br />
If there location name has changed because of changes in administrative boundaries, try to find the old name and use that.<br />
<br />
<!--T:52--><br />
If the detailed location is not known, enter as much information as is available (at least the province and kabupaten)<br />
<br />
=====Kode lokasi===== <!--T:53--><br />
This is automatically generated from the information supplied above. You cannot edit this.<br />
<br />
=====Jenis Pengirim===== <!--T:54--><br />
Required. Pick from the drop down list.<br />
<br />
=====Nama Pengirim===== <!--T:55--><br />
Optional. This is included on the client report<br />
<br />
=====Alamat Pengirim===== <!--T:56--><br />
Optional. This is included on the client report<br />
<br />
=====Nomor HP Pengirim===== <!--T:57--><br />
Optional. If available, enter the mobile phone number. This is used to identify the submitter so that it is possible to link all their submissions for consolidated reporting.<br />
<br />
=====Nama Pemilik===== <!--T:58--><br />
Optional. This is included on the client report<br />
<br />
=====Alamat Pemilik===== <!--T:59--><br />
Optional. This is included on the client report<br />
<br />
=====Nomor HP Pemilik===== <!--T:60--><br />
Optional. If available, enter the mobile number. This allows different submissions from the same owner to be linked.<br />
<br />
====Spesimen dan uji==== <!--T:61--><br />
Information about the specimen and test. Each separate specimen and test combination should be entered in a different column.<br />
<br />
<!--T:62--><br />
[[image:multitests.png]]<br />
<br />
<!--T:63--><br />
If there are multiple qualitative findings for a particular test (see below), these should be entered in new columns with the other details blank)<br />
<br />
=====Kelompok spesimen and Jenis specsimen===== <!--T:64--><br />
Required. Use these two fields to select the type of specimen (what it is or what part of the animal it came from)<br />
<br />
=====Bentuk spesimen===== <!--T:65--><br />
Required. This indicates how the specimen has been handled, prepared or treated. This may be the way it is collected (swab) prepared (smear) or preserved (formalin).<br />
<br />
=====Jenis Uji===== <!--T:66--><br />
Required. This specifies the lab section conducting the test. The tests listed in the next drop down depend on the custom list of tests for each laboratory and lab section (see below).<br />
<br />
=====Uji===== <!--T:67--><br />
Required. The test performed.<br />
<br />
=====Temuan kual.===== <!--T:68--><br />
The qualitative finding of a test. If a test produces one or more qualitative findings (e.g. bacterial or parasite species detected, or histopathological findings) each finding should be entered into a separate column on row 29. One test can therefore have multiple findings and use multiple columns.<br />
<br />
<!--T:69--><br />
[[image:qualfindings.png]]<br />
<br />
====Animal details==== <!--T:70--><br />
The bottom of the template contains information about each animal. There should be one animal per row. Each animal must have results for every test.<br />
<br />
=====Jenis kelamin===== <!--T:71--><br />
Optional.Enter the sex of each animal, if known<br />
<br />
=====Umur and Unit Umur===== <!--T:72--><br />
Optional. Enter the age of each animal, if known. The age is split into two columns. The first column (Umur) contains only numbers (whole numbers or decimals). The second column contains the units (days, weeks, months or years), selected from the drop down list. Only one unit can be used, so if an animal is 2 years and 3 months, enter the age as 2.25 years.<br />
<br />
<!--T:73--><br />
You cannot use other symbols such as > 3. Use your best estimate if the age is unknown.<br />
<br />
=====Spesies===== <!--T:74--><br />
Required. Pick from the list.<br />
<br />
=====Ras===== <!--T:75--><br />
Optional. Some species have a number of different breeds available. Add this if it is known. Sometimes there are different options - for exmaple, cattle (sapi) can be identified as beef (potong) or dairy (perah), or can be classified by their breed (limousin, friesian). Use the most detailed information known.<br />
<br />
=====ID hewan===== <!--T:76--><br />
Required. If the animals are individually uniquely identified (for example, with ear tags) then use these identifiers. If no information is available, you can simply give each animal a serial number starting at 1. <br />
<br />
<!--T:77--><br />
If the animals are in a mixed group, you can add other information in this field. For example, if they come from several owners, you could identify each animal with the owner name and the animal number.<br />
<br />
=====Temuan kuant.===== <!--T:78--><br />
Quantitative finding. This is required for tests that produce quantitative outputs. It must be a whole number or a decimal number.<br />
<br />
<!--T:79--><br />
There is a plan to allow ''uncertainty qualifiers'', such as > (greater than), < (less than), ~ approximately, however this feature has not yet been implemented.<br />
<br />
=====Hasil===== <!--T:80--><br />
Required. Pick from the drop down list.<br />
<br />
==Submitting data== <!--T:81--><br />
===Saving and sending the data===<br />
# Once data entry is complete, save the template spreadsheet to your local hard drive. You may want to change the name using the Epi Number to make finding the data again easier. <br />
# Create a new e-mail<br />
# The address should be '''labdata@isikhnas.com'''<br />
# Type the Epi number in the subject line (this is optional but will help you keep track of which data has been submitted and which hasn't, when you look at your 'sent mail' folder)<br />
# Attach the template spreadsheet that you just saved<br />
# Send the e-mail<br />
<br />
<!--T:82--><br />
If you have a local e-mail client installed on your computer (such as Thunderbird or Outlook), sending messages can be made faster and easier:<br />
# In Excel go to the File menu, select '''Save and send''', then click on the '''Send as attachment''' button. This automatically creates an email with the file attached. <br />
# Enter the address '''labdata@isikhnas.com''' and click send<br />
<br />
===Responses from iSIKHNAS=== <!--T:83--><br />
Whenever data is submitted to iSIKHNAS, there will be an automatic response which should arrive within a minute or two. The contents of the response depends on the data sent:<br />
<br />
====Successful submission - client report==== <!--T:84--><br />
If the data is all correct, then it will be automatically inserted into iSIKHNAS. <br />
<br />
<!--T:85--><br />
You will then receive an email confirming that the data has been accepted, with a summary of the data.<br />
<br />
<!--T:86--><br />
You will also receive a second email containing an automatically generated client report. This is in ODT format which can be opened and edited in [https://www.libreoffice.org Libre Office Writer] (free) or in Microsoft Word.<br />
<br />
<!--T:87--><br />
[[image:clientreport.png]]<br />
<br />
<!--T:88--><br />
Once the file has been opened, you can add any further details, save it, and print it.<br />
<br />
====Errors detected in the data==== <!--T:89--><br />
If there are any errors in the submitted data, you will receive an email listing the errors and cell references. <br />
<br />
<!--T:90--><br />
[[image:errorhighlight.png]]<br />
<br />
<!--T:91--><br />
The email will also have an attachment which is copy of the spreadsheet submitted. In this spreadsheet, the cells with errors are highlighted in yellow, with pop-up comments to explain the error.<br />
<br />
<!--T:92--><br />
If there were errors, fix these in your original spreadsheet and submit again in a new email.<br />
<br />
====System errors==== <!--T:93--><br />
If there is an error in the system, you may receive an email with a system error message, instructing you to contact your coordinator. <br />
<br />
<!--T:94--><br />
Forward the message to your iSIKHNAS coordinator or one of the iSIKHNAS champions who will help solve the problem.<br />
<br />
==Customising test details for your lab== <!--T:95--><br />
The list of laboratory sections, and tests performed by each of those sections, needs to be customised for each different laboratory.<br />
<br />
<!--T:96--><br />
To set up the list of tests, log in to the iSIKHNAS web site and go to Manage | Laboratory Tests.<br />
<br />
<!--T:97--><br />
[[image:managelabtests.png]]<br />
<br />
<!--T:98--><br />
# Choose the test from the drop down list. These are national standards so if there is a test that is not present, you must contact the iSIKHNAS champions to update the standards.<br />
# Choose the laboratory section that does the test<br />
# Choose your laboratory from the list<br />
# If the test has a qualitative finding, check the box. For example, bacterial or parasitic identification produce qualitative findings - the names of the bacteria or parasites, while an AI ELISA doesn't - it is always just testing for AI. <br />
# If the test produces a quantitative finding, check the box. For example, an ELISA produces an optical density which is a number (quantitative), a faecal egg count produces a number. However a Rose Bengal Test just has either positive or negative result, so no quantitative finding. <br />
# If a quantitative finding is produced, select the units from the list<br />
# If your lab is officially accredited to perform this test, check the box<br />
# Enter a reference to the specific method used in the test (to be printed on the client report)<br />
<br />
==Updating data standards== <!--T:99--><br />
The national laboratory standards are managed centrally to ensure consistency and the ability to analyse the data automatically. iSIKHNAS enforces these standards, so that it is not permissible to submit data that does not use the standards.<br />
<br />
<!--T:100--><br />
The standards cover all aspects of the data managed, including:<br />
* species<br />
* tests<br />
* findings<br />
* animal sex and ages<br />
* specimens<br />
<br />
<!--T:101--><br />
These standards are contained in the '''lab standards.xlsx''' spreadsheet and are available in the drop down lists on the submission template. <br />
<br />
<!--T:102--><br />
If you ever find that there is a value missing from the standard list, it is possible to have new values added. To ensure that there is consistency, this process is managed by the iSIKHNAS champions. <br />
<br />
<!--T:103--><br />
Please contact the iSIKHNAS champions to request a new value to be added to the standards.<br />
</translate></div>Angushttp://wiki.isikhnas.com/index.php?title=File:ISIKHNAS_submission_spreadsheet_v5.7.xlsx&diff=35899File:ISIKHNAS submission spreadsheet v5.7.xlsx2015-05-07T04:07:25Z<p>Angus: </p>
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<div></div>Angushttp://wiki.isikhnas.com/index.php?title=File:ISIKHNAS_submission_spreadsheet_v5.6.xlsx&diff=35897File:ISIKHNAS submission spreadsheet v5.6.xlsx2015-05-07T04:00:35Z<p>Angus: </p>
<hr />
<div></div>Angushttp://wiki.isikhnas.com/index.php?title=Spreadsheet_data_submission_manual&diff=34910Spreadsheet data submission manual2015-04-28T07:29:49Z<p>Angus: </p>
<hr />
<div><languages/><br />
<translate><br />
=Manual for spreadsheet data submission= <!--T:1--><br />
This manual provides guidance for the submission of laboratory data to iSIKHNAS using and Excel spreadsheet. <br />
<br />
==Introduction and overview== <!--T:2--><br />
The overall process is simple:<br />
* Open the spreadsheet template (and the linked data standards spreadsheet)<br />
* Enter the lab submission data <br />
* Send the spreadsheet by email to iSIKHNAS<br />
<br />
<!--T:3--><br />
iSIKHNAS automatically checks the data and, if it is valid, inserts it into the national database. An email is sent with confirmation that the data has been correctly submitted, as well as an automatically generated client report for printing in the lab.<br />
<br />
<!--T:4--><br />
To use the system, laboratory staff must:<br />
* register with iSIKHNAS (talk to your local coordinator)<br />
* have permissions set to be allowed to submit laboratory data (again, talk to your coordinator)<br />
* set up their computer<br />
** get a copy of the submission template<br />
** get a copy of the lab standards spreadsheet<br />
<br />
<!--T:5--><br />
As the system works with Excel and email, you naturally must have <br />
* a recent copy of Excel installed on your computer (one that can handle the newer '.xlsx' file formats), and<br />
* an email address and internet connection to send and receive emails. To send and receive emails you can use <br />
** a web-mail interface (like gmail) through a web browser (like Chrome, Internet Explorer or Firefox), or<br />
** an email client (like Microsoft Outlook or Thunderbird)<br />
<br />
==Setting up== <!--T:6--><br />
To be able to use the system you must have two spreadsheets:<br />
# the template<br />
# 'lab standards.xlsx' - which contains the Indonesian national laboratory data standards to ensure that all data is compatible and able to be analysed.<br />
<br />
<!--T:7--><br />
Both can be downloaded from the iSIKHNAS web site<br />
<br />
====Data submission template spreadsheet==== <!--T:8--><br />
[[image:labdatatemplate.png]]<br />
<br />
<!--T:9--><br />
This is used to enter the data, and is sent by email to iSIKHNAS.<br />
Click on the link below to download the latest version of the data submission spreadsheet:<br />
<br />
<!--T:10--><br />
[[media:ISIKHNAS submission spreadsheet v5.6.xlsx|Submission spreadsheet]]<br />
<br />
<!--T:11--><br />
The template may be updated from time to time. Your iSIKHNAS coordinator will either send you the updated spreadsheet by email, or let you know that a new version is available on this web site for download.<br />
<br />
===Laboratory standards spreadsheet=== <!--T:12--><br />
[[image:labstandards.png]]<br />
<br />
<!--T:13--><br />
The '''lab standards.xlsx''' file is automatically linked to the template, to ensure that all data submitted conforms to the national data standards. This is automatically customised for each different lab, and is generated by iSIKHNAS. Once it is generated and downloaded, you never need to edit it. If changes are required, they can be made on-line on the iSIKHNAS web site, and a new version downloaded. <br />
<br />
<!--T:14--><br />
The spreadsheet can be downloaded from the iSIKHNAS secure web site. Log in and go to:<br />
* Manage | Export Lab standards<br />
or click on the following link to go straight to the download page (you must already be logged in for this link to work)<br />
<br />
<!--T:15--><br />
https://www.isikhnas.com/en/exportlabstandards<br />
<br />
<!--T:16--><br />
[[image:exportstandards.png]]<br />
<br />
<!--T:17--><br />
# Select 'Custom lab references'<br />
# Select your lab from the drop down list<br />
# Either<br />
## Click on 'Export'<br />
### This will send a copy of the standards to your registered email address, or<br />
## Click on 'Export to lab contact'<br />
### This will send a copy to the lab contact person, as recorded in the iSIKHNAS list of laboratories (infrastructure table).<br />
<br />
===Important tips for spreadsheet management=== <!--T:18--><br />
<br />
<!--T:19--><br />
{{hlbox|Always save the template spreadsheet and the standards spreadsheet in the '''same directory'''}}<br />
<br />
<!--T:20--><br />
If they are in different directories, the automatic links will not work.<br />
<br />
<!--T:21--><br />
{{hlbox|The standards spreadsheet must always have the same name: '''lab standards.xlsx'''.}}<br />
<br />
<!--T:22--><br />
If the name is changed, it will not work.<br />
<br />
<!--T:23--><br />
When you download the standards spreadsheet from the web, sometimes your computer will automatically change the name to something like '''lab standards(2).xlsx'''. If this happens, you need to delete the old copy, and rename the file back to '''lab standards.xlsx''' as well as placing it in the correct directory.<br />
<br />
<!--T:24--><br />
{{hlbox|You can copy and rename the template file as many times as you like (but not the standards file)}}<br />
<br />
<!--T:25--><br />
You may want to keep a copy of every submission you send, so saving each file with the epi number is a good way to keep track of the files. They can all be in the same directory, as long as the '''lab standards.xlsx''' file is in the same directory.<br />
<br />
==Entering data== <!--T:26--><br />
To enter data into the template spreadsheet:<br />
# Open the '''lab standards.xlsx''' spreadsheet<br />
# Open the template spreadsheet<br />
<br />
<!--T:27--><br />
{{hlbox|Both spreadsheets must be open at the same time so that template can successfully link to the standards spreadsheet}}<br />
<br />
<!--T:28--><br />
Enter data into the required cells by clicking on the cell and typing, or clicking on the arrow to select from the drop-down list.<br />
<br />
====Controlled cells==== <!--T:29--><br />
The spreadsheet is protected to avoid entering data in the wrong places. You can only select cells intended for data entry<br />
<br />
=====Drop down lists===== <!--T:30--><br />
[[image:dropdownlist.png]]<br />
<br />
<!--T:31--><br />
There are many cells with drop down lists. These ensure that data follows the national laboratory data standards. You can only choose one of the values from the list<br />
<br />
=====Required values===== <!--T:32--><br />
[[image:requiredcell.png]]<br />
<br />
<!--T:33--><br />
When a value is required but missing, the cell is highlighted with a red border.<br />
<br />
===Hints=== <!--T:34--><br />
[[image:hintmarker.png]]<br />
<br />
<!--T:35--><br />
Many cells contain hints to guide you. These are marked with a small triangle in the corner of the cell.<br />
<br />
<!--T:36--><br />
[[image:hint.png]]<br />
<br />
<!--T:37--><br />
To view the hint, float your mouse over the triangle and the text will pop up.<br />
<br />
==Findings, results, diagnosis== <!--T:38--><br />
In iSIKHNAS each of these has a special meaning.<br />
<br />
=====Findings===== <!--T:39--><br />
This is what the lab test tells you. Findings can be <br />
* qualitative (for example, Coliforms were detected in a sample ) or <br />
* quantitative (an HI test gave a titre of 1/40)<br />
Some tests may give both qualitative and quantitative findings (for example a faecal sample contained 300 Strongyloides eggs per gram)<br />
<br />
=====Result===== <!--T:40--><br />
This is our ''interpretation'' of what the findings mean. Normally the result is either positive or negative. For example, the finding for an antibody ELISA may be an optical density of 200. If we use a cut-off of 150, this means that our interpretation of the finding is that the animal is positive - it has antibodies to the pathogen. Other possible results include ''protective'' or ''non-protective'' when doing post-vaccination surveillance; ''within acceptable limits'' or ''outside acceptable limits'' (food safety testing); light, medium or heavy load (worm eggs).<br />
<br />
=====Diagnosis===== <!--T:41--><br />
This is our conclusion, based on all the available information, as to what disease is causing the problem. A diagnosis is only meaningful when disease is present and the purpose of the submission is diagnostic. Some key points:<br />
* For surveillance, movement or other purposes, there is no diagnosis as there is no (known) disease<br />
* AI negative is ''not'' a diagnosis. It is a result (our interpretation of the information that the test gave). It does not tell us what disease is causing the problem.<br />
<br />
==Guidelines for specific fields== <!--T:42--><br />
====Pengajuan uji laboratorium====<br />
Information about the submission.<br />
<br />
=====Nomor Epi===== <!--T:43--><br />
Required. A unique submission number assigned by the laboratory.<br />
<br />
<!--T:44--><br />
When samples are sent from one laboratory to another, the original epi number should always be used (do not create a new one in the referral lab).<br />
<br />
=====Tujuan===== <!--T:45--><br />
Required. The reason for submission of the specimen.<br />
<br />
=====ID kejadian iSIKHNAS===== <!--T:46--><br />
Required for some reasons. This is the iSIKHNAS reference number, to link laboratory data to other data in iSIKHNAS.<br />
<br />
<!--T:47--><br />
This is should be used for:<br />
* Diagnostic cases: The iSIKHNAS case ID<br />
* Movement permits: The iSIKHNAS SKKH ID<br />
* Surveillance: The iSIKHNAS surveillance program ID<br />
* Post vaccination monitoring: The iSIKHNAS vaccination program ID<br />
<br />
<!--T:48--><br />
While iSIKHNAS is being rolled out, not all kabupaten will be using it, so some submissions will not have an iSIKHNAS ID even if they are meant to. In this case, leave the field empty<br />
<br />
====Pemilik dan pengirim==== <!--T:49--><br />
Information about the location, submitter and owner. The location should always be the location of the animal.<br />
<br />
=====Lokasi (PKKD)===== <!--T:50--><br />
Required. Select the location from the four drop down lists.<br />
<br />
<!--T:51--><br />
If there location name has changed because of changes in administrative boundaries, try to find the old name and use that.<br />
<br />
<!--T:52--><br />
If the detailed location is not known, enter as much information as is available (at least the province and kabupaten)<br />
<br />
=====Kode lokasi===== <!--T:53--><br />
This is automatically generated from the information supplied above. You cannot edit this.<br />
<br />
=====Jenis Pengirim===== <!--T:54--><br />
Required. Pick from the drop down list.<br />
<br />
=====Nama Pengirim===== <!--T:55--><br />
Optional. This is included on the client report<br />
<br />
=====Alamat Pengirim===== <!--T:56--><br />
Optional. This is included on the client report<br />
<br />
=====Nomor HP Pengirim===== <!--T:57--><br />
Optional. If available, enter the mobile phone number. This is used to identify the submitter so that it is possible to link all their submissions for consolidated reporting.<br />
<br />
=====Nama Pemilik===== <!--T:58--><br />
Optional. This is included on the client report<br />
<br />
=====Alamat Pemilik===== <!--T:59--><br />
Optional. This is included on the client report<br />
<br />
=====Nomor HP Pemilik===== <!--T:60--><br />
Optional. If available, enter the mobile number. This allows different submissions from the same owner to be linked.<br />
<br />
====Spesimen dan uji==== <!--T:61--><br />
Information about the specimen and test. Each separate specimen and test combination should be entered in a different column.<br />
<br />
<!--T:62--><br />
[[image:multitests.png]]<br />
<br />
<!--T:63--><br />
If there are multiple qualitative findings for a particular test (see below), these should be entered in new columns with the other details blank)<br />
<br />
=====Kelompok spesimen and Jenis specsimen===== <!--T:64--><br />
Required. Use these two fields to select the type of specimen (what it is or what part of the animal it came from)<br />
<br />
=====Bentuk spesimen===== <!--T:65--><br />
Required. This indicates how the specimen has been handled, prepared or treated. This may be the way it is collected (swab) prepared (smear) or preserved (formalin).<br />
<br />
=====Jenis Uji===== <!--T:66--><br />
Required. This specifies the lab section conducting the test. The tests listed in the next drop down depend on the custom list of tests for each laboratory and lab section (see below).<br />
<br />
=====Uji===== <!--T:67--><br />
Required. The test performed.<br />
<br />
=====Temuan kual.===== <!--T:68--><br />
The qualitative finding of a test. If a test produces one or more qualitative findings (e.g. bacterial or parasite species detected, or histopathological findings) each finding should be entered into a separate column on row 29. One test can therefore have multiple findings and use multiple columns.<br />
<br />
<!--T:69--><br />
[[image:qualfindings.png]]<br />
<br />
====Animal details==== <!--T:70--><br />
The bottom of the template contains information about each animal. There should be one animal per row. Each animal must have results for every test.<br />
<br />
=====Jenis kelamin===== <!--T:71--><br />
Optional.Enter the sex of each animal, if known<br />
<br />
=====Umur and Unit Umur===== <!--T:72--><br />
Optional. Enter the age of each animal, if known. The age is split into two columns. The first column (Umur) contains only numbers (whole numbers or decimals). The second column contains the units (days, weeks, months or years), selected from the drop down list. Only one unit can be used, so if an animal is 2 years and 3 months, enter the age as 2.25 years.<br />
<br />
<!--T:73--><br />
You cannot use other symbols such as > 3. Use your best estimate if the age is unknown.<br />
<br />
=====Spesies===== <!--T:74--><br />
Required. Pick from the list.<br />
<br />
=====Ras===== <!--T:75--><br />
Optional. Some species have a number of different breeds available. Add this if it is known. Sometimes there are different options - for exmaple, cattle (sapi) can be identified as beef (potong) or dairy (perah), or can be classified by their breed (limousin, friesian). Use the most detailed information known.<br />
<br />
=====ID hewan===== <!--T:76--><br />
Required. If the animals are individually uniquely identified (for example, with ear tags) then use these identifiers. If no information is available, you can simply give each animal a serial number starting at 1. <br />
<br />
<!--T:77--><br />
If the animals are in a mixed group, you can add other information in this field. For example, if they come from several owners, you could identify each animal with the owner name and the animal number.<br />
<br />
=====Temuan kuant.===== <!--T:78--><br />
Quantitative finding. This is required for tests that produce quantitative outputs. It must be a whole number or a decimal number.<br />
<br />
<!--T:79--><br />
There is a plan to allow ''uncertainty qualifiers'', such as > (greater than), < (less than), ~ approximately, however this feature has not yet been implemented.<br />
<br />
=====Hasil===== <!--T:80--><br />
Required. Pick from the drop down list.<br />
<br />
==Submitting data== <!--T:81--><br />
===Saving and sending the data===<br />
# Once data entry is complete, save the template spreadsheet to your local hard drive. You may want to change the name using the Epi Number to make finding the data again easier. <br />
# Create a new e-mail<br />
# The address should be '''labdata@isikhnas.com'''<br />
# Type the Epi number in the subject line (this is optional but will help you keep track of which data has been submitted and which hasn't, when you look at your 'sent mail' folder)<br />
# Attach the template spreadsheet that you just saved<br />
# Send the e-mail<br />
<br />
<!--T:82--><br />
If you have a local e-mail client installed on your computer (such as Thunderbird or Outlook), sending messages can be made faster and easier:<br />
# In Excel go to the File menu, select '''Save and send''', then click on the '''Send as attachment''' button. This automatically creates an email with the file attached. <br />
# Enter the address '''labdata@isikhnas.com''' and click send<br />
<br />
===Responses from iSIKHNAS=== <!--T:83--><br />
Whenever data is submitted to iSIKHNAS, there will be an automatic response which should arrive within a minute or two. The contents of the response depends on the data sent:<br />
<br />
====Successful submission - client report==== <!--T:84--><br />
If the data is all correct, then it will be automatically inserted into iSIKHNAS. <br />
<br />
<!--T:85--><br />
You will then receive an email confirming that the data has been accepted, with a summary of the data.<br />
<br />
<!--T:86--><br />
You will also receive a second email containing an automatically generated client report. This is in ODT format which can be opened and edited in [https://www.libreoffice.org Libre Office Writer] (free) or in Microsoft Word.<br />
<br />
<!--T:87--><br />
[[image:clientreport.png]]<br />
<br />
<!--T:88--><br />
Once the file has been opened, you can add any further details, save it, and print it.<br />
<br />
====Errors detected in the data==== <!--T:89--><br />
If there are any errors in the submitted data, you will receive an email listing the errors and cell references. <br />
<br />
<!--T:90--><br />
[[image:errorhighlight.png]]<br />
<br />
<!--T:91--><br />
The email will also have an attachment which is copy of the spreadsheet submitted. In this spreadsheet, the cells with errors are highlighted in yellow, with pop-up comments to explain the error.<br />
<br />
<!--T:92--><br />
If there were errors, fix these in your original spreadsheet and submit again in a new email.<br />
<br />
====System errors==== <!--T:93--><br />
If there is an error in the system, you may receive an email with a system error message, instructing you to contact your coordinator. <br />
<br />
<!--T:94--><br />
Forward the message to your iSIKHNAS coordinator or one of the iSIKHNAS champions who will help solve the problem.<br />
<br />
==Customising test details for your lab== <!--T:95--><br />
The list of laboratory sections, and tests performed by each of those sections, needs to be customised for each different laboratory.<br />
<br />
<!--T:96--><br />
To set up the list of tests, log in to the iSIKHNAS web site and go to Manage | Laboratory Tests.<br />
<br />
<!--T:97--><br />
[[image:managelabtests.png]]<br />
<br />
<!--T:98--><br />
# Choose the test from the drop down list. These are national standards so if there is a test that is not present, you must contact the iSIKHNAS champions to update the standards.<br />
# Choose the laboratory section that does the test<br />
# Choose your laboratory from the list<br />
# If the test has a qualitative finding, check the box. For example, bacterial or parasitic identification produce qualitative findings - the names of the bacteria or parasites, while an AI ELISA doesn't - it is always just testing for AI. <br />
# If the test produces a quantitative finding, check the box. For example, an ELISA produces an optical density which is a number (quantitative), a faecal egg count produces a number. However a Rose Bengal Test just has either positive or negative result, so no quantitative finding. <br />
# If a quantitative finding is produced, select the units from the list<br />
# If your lab is officially accredited to perform this test, check the box<br />
# Enter a reference to the specific method used in the test (to be printed on the client report)<br />
<br />
==Updating data standards== <!--T:99--><br />
The national laboratory standards are managed centrally to ensure consistency and the ability to analyse the data automatically. iSIKHNAS enforces these standards, so that it is not permissible to submit data that does not use the standards.<br />
<br />
<!--T:100--><br />
The standards cover all aspects of the data managed, including:<br />
* species<br />
* tests<br />
* findings<br />
* animal sex and ages<br />
* specimens<br />
<br />
<!--T:101--><br />
These standards are contained in the '''lab standards.xlsx''' spreadsheet and are available in the drop down lists on the submission template. <br />
<br />
<!--T:102--><br />
If you ever find that there is a value missing from the standard list, it is possible to have new values added. To ensure that there is consistency, this process is managed by the iSIKHNAS champions. <br />
<br />
<!--T:103--><br />
Please contact the iSIKHNAS champions to request a new value to be added to the standards.<br />
</translate></div>Angushttp://wiki.isikhnas.com/index.php?title=Mapping&diff=33167Mapping2015-04-04T07:27:22Z<p>Angus: /* Field names */</p>
<hr />
<div>=Mapping=<br />
The mapping system allows administrators to define new map-based reports rapidly through the interface, and for them to be viewed on-line.<br />
<br />
==Defining a new map==<br />
Maps are defined in the same way as other reports, using the Administration | Reports menu. There are two key differences compared to other reports: requirements for the SQL data definition, and style information (Mapfile code)<br />
<br />
===SQL===<br />
The SQL is similar to all other reports, and should be a single SELECT query. However, there are several particular requirements<br />
<br />
====Required fields====<br />
Every query must return two required fields:<br />
* '''gid''' - this is a 'geographic ID' and is a unique integer for each spatial unit returned. Often, this can just be the id from the locations table, but if there can be multiple reports per location, you need to choose another unique ID value. It doesn't matter which. If nothing else is available, you can also use the row number window function:<br />
select row_number() over () as gid, <br />
* '''the_geom''': this is the spatial data and must be included in every report. It should always come from the projected version of the locations table spatial data. That is:<br />
** For polygon data (administrative units) this should be geom_proj (e.g. select geom_proj as the_geom, )<br />
** For point data (village locations etc) this should be centroid_proj (e.g. select centroid_proj as the_geom, )<br />
Don't use the standard geom and centroid columns, or the data will not be in the right projection and won't appear on the map.<br />
<br />
===Field names===<br />
Any fields generated in the query will be available to the user with a map query (where they click on a feature, and further information pops up). So that this feature works nicely, you should include all the data that a user might want to see, and name each field with a user-friendly name. For example<br />
SELECT<br />
sum(total) as "Julah hewan"<br />
<br />
===Example===<br />
An example of a simple query to display infrastructure:<br />
SELECT<br />
i.id as gid,<br />
l.centroid_proj as the_geom,<br />
i.shortname as "Nama infrastruktur",<br />
from infrastructure i<br />
join locations l on i.locationid = l.id<br />
where not i.del<br />
<br />
===Mapfile code===<br />
The R code box of the Report definition interface is used to include mapfile code, which specifies the appearance of the output. <br />
<br />
Most of the mapfile is automatically generated using fixed standards and the SQL previously defined, but you have to specify here how the map should appear.<br />
<br />
The contents of the R code box, are inserted into the mapfile in a LAYER block. Full documentation of what is permitted can be found in the [http://mapserver.org/mapfile/layer.html Mapserver documentation]<br />
<br />
Two sections are required (TYPE and CLASS) and there are some optional sections<br />
=====TYPE (required)=====<br />
This can be POINT, LINE or POLYGON, depending on the map to be produced. For example, for a point map:<br />
TYPE POINT<br />
Other types can be used including CHART, CIRCLE, RASTER, but these are uncommon advanced features. <br />
<br />
=====CLASS (required) =====<br />
This defines the appearance of the data, as well as the legend. A typical class block for a point map <br />
CLASS<br />
NAME "Kasus"<br />
STYLE<br />
SYMBOL "reddot"<br />
END # STYLE<br />
END # CLASS<br />
<br />
This will produce a layer with a single symbol (reddot) for all features, and a legend with 'Kasus'.<br />
<br />
For a polygon layer, you can define the colour of the outline and the fill:<br />
CLASS<br />
NAME "Pelatihan"<br />
STYLE<br />
COLOR 255 0 0<br />
OUTLINECOLOR 255 0 0<br />
SIZE 6<br />
END # STYLE<br />
END<br />
<br />
The style options are very powerful. See the [http://mapserver.org/mapfile/class.html#class Mapserver CLASS documentation] for more information.<br />
<br />
Standard SYMBOLs are pre-defined in a symbol file. For more symbols, this file will have to be manually edited.<br />
<br />
It is also possible to define multiple levels of shading, by referring to data from the query. For example:<br />
<br />
CLASS<br />
NAME "Belum gunakan"<br />
EXPRESSION ([laporan] = 0)<br />
STYLE<br />
COLOR 237 248 251<br />
END # STYLE<br />
END # CLASS<br />
<br />
CLASS<br />
NAME "1 - 5 laporan"<br />
EXPRESSION ([laporan] > 0 AND [laporan] < 6)<br />
STYLE<br />
COLOR 178 226 226<br />
END # STYLE<br />
END # CLASS<br />
<br />
CLASS<br />
NAME "6 - 50 laporan"<br />
EXPRESSION ([laporan] > 5 AND [laporan] < 50)<br />
STYLE<br />
COLOR 102 194 164<br />
END # STYLE<br />
END # CLASS<br />
<br />
CLASS<br />
NAME "> 50 laporan"<br />
EXPRESSION ([laporan] > 50)<br />
STYLE<br />
COLOR 35 139 69<br />
END # STYLE<br />
END # CLASS<br />
<br />
In this case, the query must have a field called "laporan" which has an integer (the number of reports submitted).<br />
<br />
The COLOR and OUTLINECOLOR lines require a RGB (red green blue) colour code. The [http://colorbrewer2.org/index.html ColorBrewer] web site is an excellent tool for picking good map colours and finding their RBG code.<br />
<br />
=====CLASSITEM (optional) =====<br />
This specifies that one field in the query will be used to determine the style of different features. For example:<br />
<br />
CLASSITEM "Hasil"<br />
CLASS<br />
NAME "Positif"<br />
EXPRESSION "Pos"<br />
STYLE<br />
SYMBOL "reddot"<br />
END<br />
END<br />
<br />
CLASS<br />
NAME "Negatif"<br />
EXPRESSION "Neg"<br />
STYLE<br />
SYMBOL "bluedot"<br />
END<br />
END<br />
<br />
This means that there must be a field in the query called "Hasil" and it will return values of either "Positif" or "Negatif"<br />
<br />
==Viewing maps==<br />
Maps must be viewed using the 'root' interface.<br />
<br />
* If there are no special parameters (the normal situation)<br />
** Set up a menu entry as usual, and set the URL to: root/index/''reportid''. For example<br />
/root/index/216<br />
<br />
* If there are parameters to produced a pre-configured report (different from the default) you need to use remove the first '/' and add the parameters. For example:<br />
<br />
root/index/216&param[diagnosis]=13</div>Angushttp://wiki.isikhnas.com/index.php?title=Mapping&diff=33166Mapping2015-04-04T07:23:50Z<p>Angus: /* Required fields */</p>
<hr />
<div>=Mapping=<br />
The mapping system allows administrators to define new map-based reports rapidly through the interface, and for them to be viewed on-line.<br />
<br />
==Defining a new map==<br />
Maps are defined in the same way as other reports, using the Administration | Reports menu. There are two key differences compared to other reports: requirements for the SQL data definition, and style information (Mapfile code)<br />
<br />
===SQL===<br />
The SQL is similar to all other reports, and should be a single SELECT query. However, there are several particular requirements<br />
<br />
====Required fields====<br />
Every query must return two required fields:<br />
* '''gid''' - this is a 'geographic ID' and is a unique integer for each spatial unit returned. Often, this can just be the id from the locations table, but if there can be multiple reports per location, you need to choose another unique ID value. It doesn't matter which. If nothing else is available, you can also use the row number window function:<br />
select row_number() over () as gid, <br />
* '''the_geom''': this is the spatial data and must be included in every report. It should always come from the projected version of the locations table spatial data. That is:<br />
** For polygon data (administrative units) this should be geom_proj (e.g. select geom_proj as the_geom, )<br />
** For point data (village locations etc) this should be centroid_proj (e.g. select centroid_proj as the_geom, )<br />
Don't use the standard geom and centroid columns, or the data will not be in the right projection and won't appear on the map.<br />
<br />
===Field names===<br />
Any fields generated in the query will be available to the user with a map query (where they click on a feature, and further information pops up). So that this feature works nicely, you should include all the data that a user might want to see, and name each field with a user-friendly name. For example<br />
SELECT<br />
sum(total) as "Julah hewan"<br />
<br />
===Mapfile code===<br />
The R code box of the Report definition interface is used to include mapfile code, which specifies the appearance of the output. <br />
<br />
Most of the mapfile is automatically generated using fixed standards and the SQL previously defined, but you have to specify here how the map should appear.<br />
<br />
The contents of the R code box, are inserted into the mapfile in a LAYER block. Full documentation of what is permitted can be found in the [http://mapserver.org/mapfile/layer.html Mapserver documentation]<br />
<br />
Two sections are required (TYPE and CLASS) and there are some optional sections<br />
=====TYPE (required)=====<br />
This can be POINT, LINE or POLYGON, depending on the map to be produced. For example, for a point map:<br />
TYPE POINT<br />
Other types can be used including CHART, CIRCLE, RASTER, but these are uncommon advanced features. <br />
<br />
=====CLASS (required) =====<br />
This defines the appearance of the data, as well as the legend. A typical class block for a point map <br />
CLASS<br />
NAME "Kasus"<br />
STYLE<br />
SYMBOL "reddot"<br />
END # STYLE<br />
END # CLASS<br />
<br />
This will produce a layer with a single symbol (reddot) for all features, and a legend with 'Kasus'.<br />
<br />
For a polygon layer, you can define the colour of the outline and the fill:<br />
CLASS<br />
NAME "Pelatihan"<br />
STYLE<br />
COLOR 255 0 0<br />
OUTLINECOLOR 255 0 0<br />
SIZE 6<br />
END # STYLE<br />
END<br />
<br />
The style options are very powerful. See the [http://mapserver.org/mapfile/class.html#class Mapserver CLASS documentation] for more information.<br />
<br />
Standard SYMBOLs are pre-defined in a symbol file. For more symbols, this file will have to be manually edited.<br />
<br />
It is also possible to define multiple levels of shading, by referring to data from the query. For example:<br />
<br />
CLASS<br />
NAME "Belum gunakan"<br />
EXPRESSION ([laporan] = 0)<br />
STYLE<br />
COLOR 237 248 251<br />
END # STYLE<br />
END # CLASS<br />
<br />
CLASS<br />
NAME "1 - 5 laporan"<br />
EXPRESSION ([laporan] > 0 AND [laporan] < 6)<br />
STYLE<br />
COLOR 178 226 226<br />
END # STYLE<br />
END # CLASS<br />
<br />
CLASS<br />
NAME "6 - 50 laporan"<br />
EXPRESSION ([laporan] > 5 AND [laporan] < 50)<br />
STYLE<br />
COLOR 102 194 164<br />
END # STYLE<br />
END # CLASS<br />
<br />
CLASS<br />
NAME "> 50 laporan"<br />
EXPRESSION ([laporan] > 50)<br />
STYLE<br />
COLOR 35 139 69<br />
END # STYLE<br />
END # CLASS<br />
<br />
In this case, the query must have a field called "laporan" which has an integer (the number of reports submitted).<br />
<br />
The COLOR and OUTLINECOLOR lines require a RGB (red green blue) colour code. The [http://colorbrewer2.org/index.html ColorBrewer] web site is an excellent tool for picking good map colours and finding their RBG code.<br />
<br />
=====CLASSITEM (optional) =====<br />
This specifies that one field in the query will be used to determine the style of different features. For example:<br />
<br />
CLASSITEM "Hasil"<br />
CLASS<br />
NAME "Positif"<br />
EXPRESSION "Pos"<br />
STYLE<br />
SYMBOL "reddot"<br />
END<br />
END<br />
<br />
CLASS<br />
NAME "Negatif"<br />
EXPRESSION "Neg"<br />
STYLE<br />
SYMBOL "bluedot"<br />
END<br />
END<br />
<br />
This means that there must be a field in the query called "Hasil" and it will return values of either "Positif" or "Negatif"<br />
<br />
==Viewing maps==<br />
Maps must be viewed using the 'root' interface.<br />
<br />
* If there are no special parameters (the normal situation)<br />
** Set up a menu entry as usual, and set the URL to: root/index/''reportid''. For example<br />
/root/index/216<br />
<br />
* If there are parameters to produced a pre-configured report (different from the default) you need to use remove the first '/' and add the parameters. For example:<br />
<br />
root/index/216&param[diagnosis]=13</div>Angushttp://wiki.isikhnas.com/index.php?title=Mapping&diff=33165Mapping2015-04-04T07:22:59Z<p>Angus: /* Viewing maps */</p>
<hr />
<div>=Mapping=<br />
The mapping system allows administrators to define new map-based reports rapidly through the interface, and for them to be viewed on-line.<br />
<br />
==Defining a new map==<br />
Maps are defined in the same way as other reports, using the Administration | Reports menu. There are two key differences compared to other reports: requirements for the SQL data definition, and style information (Mapfile code)<br />
<br />
===SQL===<br />
The SQL is similar to all other reports, and should be a single SELECT query. However, there are several particular requirements<br />
<br />
====Required fields====<br />
Every query must return two required fields:<br />
* gid - this is a 'geographic ID' and is a unique integer for each spatial unit returned. Often, this can just be the id from the locations table, but if there can be multiple reports per location, you need to choose another unique ID value. It doesn't matter which. If nothing else is available, you can also use the row number window function:<br />
select row_number() over () as gid, <br />
* the_geom: this is the spatial data and must be included in every report. It should always come from the projected version of the locations table spatial data. That is:<br />
** For polygon data (administrative units) this should be geom_proj (e.g. select geom_proj as the_geom, )<br />
** For point data (village locations etc) this should be centroid_proj (e.g. select centroid_proj as the_geom, )<br />
Don't use the standard geom and centroid columns, or the data will not be in the right projection and won't appear on the map.<br />
<br />
===Field names===<br />
Any fields generated in the query will be available to the user with a map query (where they click on a feature, and further information pops up). So that this feature works nicely, you should include all the data that a user might want to see, and name each field with a user-friendly name. For example<br />
SELECT<br />
sum(total) as "Julah hewan"<br />
<br />
===Mapfile code===<br />
The R code box of the Report definition interface is used to include mapfile code, which specifies the appearance of the output. <br />
<br />
Most of the mapfile is automatically generated using fixed standards and the SQL previously defined, but you have to specify here how the map should appear.<br />
<br />
The contents of the R code box, are inserted into the mapfile in a LAYER block. Full documentation of what is permitted can be found in the [http://mapserver.org/mapfile/layer.html Mapserver documentation]<br />
<br />
Two sections are required (TYPE and CLASS) and there are some optional sections<br />
=====TYPE (required)=====<br />
This can be POINT, LINE or POLYGON, depending on the map to be produced. For example, for a point map:<br />
TYPE POINT<br />
Other types can be used including CHART, CIRCLE, RASTER, but these are uncommon advanced features. <br />
<br />
=====CLASS (required) =====<br />
This defines the appearance of the data, as well as the legend. A typical class block for a point map <br />
CLASS<br />
NAME "Kasus"<br />
STYLE<br />
SYMBOL "reddot"<br />
END # STYLE<br />
END # CLASS<br />
<br />
This will produce a layer with a single symbol (reddot) for all features, and a legend with 'Kasus'.<br />
<br />
For a polygon layer, you can define the colour of the outline and the fill:<br />
CLASS<br />
NAME "Pelatihan"<br />
STYLE<br />
COLOR 255 0 0<br />
OUTLINECOLOR 255 0 0<br />
SIZE 6<br />
END # STYLE<br />
END<br />
<br />
The style options are very powerful. See the [http://mapserver.org/mapfile/class.html#class Mapserver CLASS documentation] for more information.<br />
<br />
Standard SYMBOLs are pre-defined in a symbol file. For more symbols, this file will have to be manually edited.<br />
<br />
It is also possible to define multiple levels of shading, by referring to data from the query. For example:<br />
<br />
CLASS<br />
NAME "Belum gunakan"<br />
EXPRESSION ([laporan] = 0)<br />
STYLE<br />
COLOR 237 248 251<br />
END # STYLE<br />
END # CLASS<br />
<br />
CLASS<br />
NAME "1 - 5 laporan"<br />
EXPRESSION ([laporan] > 0 AND [laporan] < 6)<br />
STYLE<br />
COLOR 178 226 226<br />
END # STYLE<br />
END # CLASS<br />
<br />
CLASS<br />
NAME "6 - 50 laporan"<br />
EXPRESSION ([laporan] > 5 AND [laporan] < 50)<br />
STYLE<br />
COLOR 102 194 164<br />
END # STYLE<br />
END # CLASS<br />
<br />
CLASS<br />
NAME "> 50 laporan"<br />
EXPRESSION ([laporan] > 50)<br />
STYLE<br />
COLOR 35 139 69<br />
END # STYLE<br />
END # CLASS<br />
<br />
In this case, the query must have a field called "laporan" which has an integer (the number of reports submitted).<br />
<br />
The COLOR and OUTLINECOLOR lines require a RGB (red green blue) colour code. The [http://colorbrewer2.org/index.html ColorBrewer] web site is an excellent tool for picking good map colours and finding their RBG code.<br />
<br />
=====CLASSITEM (optional) =====<br />
This specifies that one field in the query will be used to determine the style of different features. For example:<br />
<br />
CLASSITEM "Hasil"<br />
CLASS<br />
NAME "Positif"<br />
EXPRESSION "Pos"<br />
STYLE<br />
SYMBOL "reddot"<br />
END<br />
END<br />
<br />
CLASS<br />
NAME "Negatif"<br />
EXPRESSION "Neg"<br />
STYLE<br />
SYMBOL "bluedot"<br />
END<br />
END<br />
<br />
This means that there must be a field in the query called "Hasil" and it will return values of either "Positif" or "Negatif"<br />
<br />
==Viewing maps==<br />
Maps must be viewed using the 'root' interface.<br />
<br />
* If there are no special parameters (the normal situation)<br />
** Set up a menu entry as usual, and set the URL to: root/index/''reportid''. For example<br />
/root/index/216<br />
<br />
* If there are parameters to produced a pre-configured report (different from the default) you need to use remove the first '/' and add the parameters. For example:<br />
<br />
root/index/216&param[diagnosis]=13</div>Angushttp://wiki.isikhnas.com/index.php?title=Mapping&diff=33164Mapping2015-04-04T07:22:13Z<p>Angus: /* CLASSITEM (optoinal) */</p>
<hr />
<div>=Mapping=<br />
The mapping system allows administrators to define new map-based reports rapidly through the interface, and for them to be viewed on-line.<br />
<br />
==Defining a new map==<br />
Maps are defined in the same way as other reports, using the Administration | Reports menu. There are two key differences compared to other reports: requirements for the SQL data definition, and style information (Mapfile code)<br />
<br />
===SQL===<br />
The SQL is similar to all other reports, and should be a single SELECT query. However, there are several particular requirements<br />
<br />
====Required fields====<br />
Every query must return two required fields:<br />
* gid - this is a 'geographic ID' and is a unique integer for each spatial unit returned. Often, this can just be the id from the locations table, but if there can be multiple reports per location, you need to choose another unique ID value. It doesn't matter which. If nothing else is available, you can also use the row number window function:<br />
select row_number() over () as gid, <br />
* the_geom: this is the spatial data and must be included in every report. It should always come from the projected version of the locations table spatial data. That is:<br />
** For polygon data (administrative units) this should be geom_proj (e.g. select geom_proj as the_geom, )<br />
** For point data (village locations etc) this should be centroid_proj (e.g. select centroid_proj as the_geom, )<br />
Don't use the standard geom and centroid columns, or the data will not be in the right projection and won't appear on the map.<br />
<br />
===Field names===<br />
Any fields generated in the query will be available to the user with a map query (where they click on a feature, and further information pops up). So that this feature works nicely, you should include all the data that a user might want to see, and name each field with a user-friendly name. For example<br />
SELECT<br />
sum(total) as "Julah hewan"<br />
<br />
===Mapfile code===<br />
The R code box of the Report definition interface is used to include mapfile code, which specifies the appearance of the output. <br />
<br />
Most of the mapfile is automatically generated using fixed standards and the SQL previously defined, but you have to specify here how the map should appear.<br />
<br />
The contents of the R code box, are inserted into the mapfile in a LAYER block. Full documentation of what is permitted can be found in the [http://mapserver.org/mapfile/layer.html Mapserver documentation]<br />
<br />
Two sections are required (TYPE and CLASS) and there are some optional sections<br />
=====TYPE (required)=====<br />
This can be POINT, LINE or POLYGON, depending on the map to be produced. For example, for a point map:<br />
TYPE POINT<br />
Other types can be used including CHART, CIRCLE, RASTER, but these are uncommon advanced features. <br />
<br />
=====CLASS (required) =====<br />
This defines the appearance of the data, as well as the legend. A typical class block for a point map <br />
CLASS<br />
NAME "Kasus"<br />
STYLE<br />
SYMBOL "reddot"<br />
END # STYLE<br />
END # CLASS<br />
<br />
This will produce a layer with a single symbol (reddot) for all features, and a legend with 'Kasus'.<br />
<br />
For a polygon layer, you can define the colour of the outline and the fill:<br />
CLASS<br />
NAME "Pelatihan"<br />
STYLE<br />
COLOR 255 0 0<br />
OUTLINECOLOR 255 0 0<br />
SIZE 6<br />
END # STYLE<br />
END<br />
<br />
The style options are very powerful. See the [http://mapserver.org/mapfile/class.html#class Mapserver CLASS documentation] for more information.<br />
<br />
Standard SYMBOLs are pre-defined in a symbol file. For more symbols, this file will have to be manually edited.<br />
<br />
It is also possible to define multiple levels of shading, by referring to data from the query. For example:<br />
<br />
CLASS<br />
NAME "Belum gunakan"<br />
EXPRESSION ([laporan] = 0)<br />
STYLE<br />
COLOR 237 248 251<br />
END # STYLE<br />
END # CLASS<br />
<br />
CLASS<br />
NAME "1 - 5 laporan"<br />
EXPRESSION ([laporan] > 0 AND [laporan] < 6)<br />
STYLE<br />
COLOR 178 226 226<br />
END # STYLE<br />
END # CLASS<br />
<br />
CLASS<br />
NAME "6 - 50 laporan"<br />
EXPRESSION ([laporan] > 5 AND [laporan] < 50)<br />
STYLE<br />
COLOR 102 194 164<br />
END # STYLE<br />
END # CLASS<br />
<br />
CLASS<br />
NAME "> 50 laporan"<br />
EXPRESSION ([laporan] > 50)<br />
STYLE<br />
COLOR 35 139 69<br />
END # STYLE<br />
END # CLASS<br />
<br />
In this case, the query must have a field called "laporan" which has an integer (the number of reports submitted).<br />
<br />
The COLOR and OUTLINECOLOR lines require a RGB (red green blue) colour code. The [http://colorbrewer2.org/index.html ColorBrewer] web site is an excellent tool for picking good map colours and finding their RBG code.<br />
<br />
=====CLASSITEM (optional) =====<br />
This specifies that one field in the query will be used to determine the style of different features. For example:<br />
<br />
CLASSITEM "Hasil"<br />
CLASS<br />
NAME "Positif"<br />
EXPRESSION "Pos"<br />
STYLE<br />
SYMBOL "reddot"<br />
END<br />
END<br />
<br />
CLASS<br />
NAME "Negatif"<br />
EXPRESSION "Neg"<br />
STYLE<br />
SYMBOL "bluedot"<br />
END<br />
END<br />
<br />
This means that there must be a field in the query called "Hasil" and it will return values of either "Positif" or "Negatif"<br />
<br />
==Viewing maps==<br />
Maps must be viewed using the 'root' interface.<br />
<br />
* If there are no special parameters (the normal situation)<br />
** Set up a menu entry as usual, and set the URL to: root/index/''reportid''. For example<br />
/root/index/216<br />
<br />
* If there are parameters to produced a pre-configured report (different from the default, you need to use remove the first '/' and add the parameters. For example:<br />
<br />
root/index/216&param[diagnosis]=13</div>Angushttp://wiki.isikhnas.com/index.php?title=Mapping&diff=33031Mapping2015-04-01T07:40:20Z<p>Angus: /* Viewing maps */</p>
<hr />
<div>=Mapping=<br />
The mapping system allows administrators to define new map-based reports rapidly through the interface, and for them to be viewed on-line.<br />
<br />
==Defining a new map==<br />
Maps are defined in the same way as other reports, using the Administration | Reports menu. There are two key differences compared to other reports: requirements for the SQL data definition, and style information (Mapfile code)<br />
<br />
===SQL===<br />
The SQL is similar to all other reports, and should be a single SELECT query. However, there are several particular requirements<br />
<br />
====Required fields====<br />
Every query must return two required fields:<br />
* gid - this is a 'geographic ID' and is a unique integer for each spatial unit returned. Often, this can just be the id from the locations table, but if there can be multiple reports per location, you need to choose another unique ID value. It doesn't matter which. If nothing else is available, you can also use the row number window function:<br />
select row_number() over () as gid, <br />
* the_geom: this is the spatial data and must be included in every report. It should always come from the projected version of the locations table spatial data. That is:<br />
** For polygon data (administrative units) this should be geom_proj (e.g. select geom_proj as the_geom, )<br />
** For point data (village locations etc) this should be centroid_proj (e.g. select centroid_proj as the_geom, )<br />
Don't use the standard geom and centroid columns, or the data will not be in the right projection and won't appear on the map.<br />
<br />
===Field names===<br />
Any fields generated in the query will be available to the user with a map query (where they click on a feature, and further information pops up). So that this feature works nicely, you should include all the data that a user might want to see, and name each field with a user-friendly name. For example<br />
SELECT<br />
sum(total) as "Julah hewan"<br />
<br />
===Mapfile code===<br />
The R code box of the Report definition interface is used to include mapfile code, which specifies the appearance of the output. <br />
<br />
Most of the mapfile is automatically generated using fixed standards and the SQL previously defined, but you have to specify here how the map should appear.<br />
<br />
The contents of the R code box, are inserted into the mapfile in a LAYER block. Full documentation of what is permitted can be found in the [http://mapserver.org/mapfile/layer.html Mapserver documentation]<br />
<br />
Two sections are required (TYPE and CLASS) and there are some optional sections<br />
=====TYPE (required)=====<br />
This can be POINT, LINE or POLYGON, depending on the map to be produced. For example, for a point map:<br />
TYPE POINT<br />
Other types can be used including CHART, CIRCLE, RASTER, but these are uncommon advanced features. <br />
<br />
=====CLASS (required) =====<br />
This defines the appearance of the data, as well as the legend. A typical class block for a point map <br />
CLASS<br />
NAME "Kasus"<br />
STYLE<br />
SYMBOL "reddot"<br />
END # STYLE<br />
END # CLASS<br />
<br />
This will produce a layer with a single symbol (reddot) for all features, and a legend with 'Kasus'.<br />
<br />
For a polygon layer, you can define the colour of the outline and the fill:<br />
CLASS<br />
NAME "Pelatihan"<br />
STYLE<br />
COLOR 255 0 0<br />
OUTLINECOLOR 255 0 0<br />
SIZE 6<br />
END # STYLE<br />
END<br />
<br />
The style options are very powerful. See the [http://mapserver.org/mapfile/class.html#class Mapserver CLASS documentation] for more information.<br />
<br />
Standard SYMBOLs are pre-defined in a symbol file. For more symbols, this file will have to be manually edited.<br />
<br />
It is also possible to define multiple levels of shading, by referring to data from the query. For example:<br />
<br />
CLASS<br />
NAME "Belum gunakan"<br />
EXPRESSION ([laporan] = 0)<br />
STYLE<br />
COLOR 237 248 251<br />
END # STYLE<br />
END # CLASS<br />
<br />
CLASS<br />
NAME "1 - 5 laporan"<br />
EXPRESSION ([laporan] > 0 AND [laporan] < 6)<br />
STYLE<br />
COLOR 178 226 226<br />
END # STYLE<br />
END # CLASS<br />
<br />
CLASS<br />
NAME "6 - 50 laporan"<br />
EXPRESSION ([laporan] > 5 AND [laporan] < 50)<br />
STYLE<br />
COLOR 102 194 164<br />
END # STYLE<br />
END # CLASS<br />
<br />
CLASS<br />
NAME "> 50 laporan"<br />
EXPRESSION ([laporan] > 50)<br />
STYLE<br />
COLOR 35 139 69<br />
END # STYLE<br />
END # CLASS<br />
<br />
In this case, the query must have a field called "laporan" which has an integer (the number of reports submitted).<br />
<br />
The COLOR and OUTLINECOLOR lines require a RGB (red green blue) colour code. The [http://colorbrewer2.org/index.html ColorBrewer] web site is an excellent tool for picking good map colours and finding their RBG code.<br />
<br />
=====CLASSITEM (optoinal) =====<br />
This specifies that one field in the query will be used to determine the style of different features. For example:<br />
<br />
CLASSITEM "Hasil"<br />
CLASS<br />
NAME "Positif"<br />
EXPRESSION "Pos"<br />
STYLE<br />
SYMBOL "reddot"<br />
END<br />
END<br />
<br />
CLASS<br />
NAME "Negatif"<br />
EXPRESSION "Neg"<br />
STYLE<br />
SYMBOL "bluedot"<br />
END<br />
END<br />
<br />
This means that there must be a field in the query called "Hasil" and it will return values of either "Positif" or "Negatif"<br />
<br />
==Viewing maps==<br />
Maps must be viewed using the 'root' interface.<br />
<br />
* If there are no special parameters (the normal situation)<br />
** Set up a menu entry as usual, and set the URL to: root/index/''reportid''. For example<br />
/root/index/216<br />
<br />
* If there are parameters to produced a pre-configured report (different from the default, you need to use remove the first '/' and add the parameters. For example:<br />
<br />
root/index/216&param[diagnosis]=13</div>Angushttp://wiki.isikhnas.com/index.php?title=Mapping&diff=33027Mapping2015-04-01T07:33:32Z<p>Angus: /* Mapfile code */</p>
<hr />
<div>=Mapping=<br />
The mapping system allows administrators to define new map-based reports rapidly through the interface, and for them to be viewed on-line.<br />
<br />
==Defining a new map==<br />
Maps are defined in the same way as other reports, using the Administration | Reports menu. There are two key differences compared to other reports: requirements for the SQL data definition, and style information (Mapfile code)<br />
<br />
===SQL===<br />
The SQL is similar to all other reports, and should be a single SELECT query. However, there are several particular requirements<br />
<br />
====Required fields====<br />
Every query must return two required fields:<br />
* gid - this is a 'geographic ID' and is a unique integer for each spatial unit returned. Often, this can just be the id from the locations table, but if there can be multiple reports per location, you need to choose another unique ID value. It doesn't matter which. If nothing else is available, you can also use the row number window function:<br />
select row_number() over () as gid, <br />
* the_geom: this is the spatial data and must be included in every report. It should always come from the projected version of the locations table spatial data. That is:<br />
** For polygon data (administrative units) this should be geom_proj (e.g. select geom_proj as the_geom, )<br />
** For point data (village locations etc) this should be centroid_proj (e.g. select centroid_proj as the_geom, )<br />
Don't use the standard geom and centroid columns, or the data will not be in the right projection and won't appear on the map.<br />
<br />
===Field names===<br />
Any fields generated in the query will be available to the user with a map query (where they click on a feature, and further information pops up). So that this feature works nicely, you should include all the data that a user might want to see, and name each field with a user-friendly name. For example<br />
SELECT<br />
sum(total) as "Julah hewan"<br />
<br />
===Mapfile code===<br />
The R code box of the Report definition interface is used to include mapfile code, which specifies the appearance of the output. <br />
<br />
Most of the mapfile is automatically generated using fixed standards and the SQL previously defined, but you have to specify here how the map should appear.<br />
<br />
The contents of the R code box, are inserted into the mapfile in a LAYER block. Full documentation of what is permitted can be found in the [http://mapserver.org/mapfile/layer.html Mapserver documentation]<br />
<br />
Two sections are required (TYPE and CLASS) and there are some optional sections<br />
=====TYPE (required)=====<br />
This can be POINT, LINE or POLYGON, depending on the map to be produced. For example, for a point map:<br />
TYPE POINT<br />
Other types can be used including CHART, CIRCLE, RASTER, but these are uncommon advanced features. <br />
<br />
=====CLASS (required) =====<br />
This defines the appearance of the data, as well as the legend. A typical class block for a point map <br />
CLASS<br />
NAME "Kasus"<br />
STYLE<br />
SYMBOL "reddot"<br />
END # STYLE<br />
END # CLASS<br />
<br />
This will produce a layer with a single symbol (reddot) for all features, and a legend with 'Kasus'.<br />
<br />
For a polygon layer, you can define the colour of the outline and the fill:<br />
CLASS<br />
NAME "Pelatihan"<br />
STYLE<br />
COLOR 255 0 0<br />
OUTLINECOLOR 255 0 0<br />
SIZE 6<br />
END # STYLE<br />
END<br />
<br />
The style options are very powerful. See the [http://mapserver.org/mapfile/class.html#class Mapserver CLASS documentation] for more information.<br />
<br />
Standard SYMBOLs are pre-defined in a symbol file. For more symbols, this file will have to be manually edited.<br />
<br />
It is also possible to define multiple levels of shading, by referring to data from the query. For example:<br />
<br />
CLASS<br />
NAME "Belum gunakan"<br />
EXPRESSION ([laporan] = 0)<br />
STYLE<br />
COLOR 237 248 251<br />
END # STYLE<br />
END # CLASS<br />
<br />
CLASS<br />
NAME "1 - 5 laporan"<br />
EXPRESSION ([laporan] > 0 AND [laporan] < 6)<br />
STYLE<br />
COLOR 178 226 226<br />
END # STYLE<br />
END # CLASS<br />
<br />
CLASS<br />
NAME "6 - 50 laporan"<br />
EXPRESSION ([laporan] > 5 AND [laporan] < 50)<br />
STYLE<br />
COLOR 102 194 164<br />
END # STYLE<br />
END # CLASS<br />
<br />
CLASS<br />
NAME "> 50 laporan"<br />
EXPRESSION ([laporan] > 50)<br />
STYLE<br />
COLOR 35 139 69<br />
END # STYLE<br />
END # CLASS<br />
<br />
In this case, the query must have a field called "laporan" which has an integer (the number of reports submitted).<br />
<br />
The COLOR and OUTLINECOLOR lines require a RGB (red green blue) colour code. The [http://colorbrewer2.org/index.html ColorBrewer] web site is an excellent tool for picking good map colours and finding their RBG code.<br />
<br />
=====CLASSITEM (optoinal) =====<br />
This specifies that one field in the query will be used to determine the style of different features. For example:<br />
<br />
CLASSITEM "Hasil"<br />
CLASS<br />
NAME "Positif"<br />
EXPRESSION "Pos"<br />
STYLE<br />
SYMBOL "reddot"<br />
END<br />
END<br />
<br />
CLASS<br />
NAME "Negatif"<br />
EXPRESSION "Neg"<br />
STYLE<br />
SYMBOL "bluedot"<br />
END<br />
END<br />
<br />
This means that there must be a field in the query called "Hasil" and it will return values of either "Positif" or "Negatif"<br />
<br />
==Viewing maps==<br />
Menu root</div>Angushttp://wiki.isikhnas.com/index.php?title=Mapping&diff=33022Mapping2015-04-01T07:28:00Z<p>Angus: /* Mapfile code */</p>
<hr />
<div>=Mapping=<br />
The mapping system allows administrators to define new map-based reports rapidly through the interface, and for them to be viewed on-line.<br />
<br />
==Defining a new map==<br />
Maps are defined in the same way as other reports, using the Administration | Reports menu. There are two key differences compared to other reports: requirements for the SQL data definition, and style information (Mapfile code)<br />
<br />
===SQL===<br />
The SQL is similar to all other reports, and should be a single SELECT query. However, there are several particular requirements<br />
<br />
====Required fields====<br />
Every query must return two required fields:<br />
* gid - this is a 'geographic ID' and is a unique integer for each spatial unit returned. Often, this can just be the id from the locations table, but if there can be multiple reports per location, you need to choose another unique ID value. It doesn't matter which. If nothing else is available, you can also use the row number window function:<br />
select row_number() over () as gid, <br />
* the_geom: this is the spatial data and must be included in every report. It should always come from the projected version of the locations table spatial data. That is:<br />
** For polygon data (administrative units) this should be geom_proj (e.g. select geom_proj as the_geom, )<br />
** For point data (village locations etc) this should be centroid_proj (e.g. select centroid_proj as the_geom, )<br />
Don't use the standard geom and centroid columns, or the data will not be in the right projection and won't appear on the map.<br />
<br />
===Field names===<br />
Any fields generated in the query will be available to the user with a map query (where they click on a feature, and further information pops up). So that this feature works nicely, you should include all the data that a user might want to see, and name each field with a user-friendly name. For example<br />
SELECT<br />
sum(total) as "Julah hewan"<br />
<br />
===Mapfile code===<br />
The R code box of the Report definition interface is used to include mapfile code, which specifies the appearance of the output. <br />
<br />
Most of the mapfile is automatically generated using fixed standards and the SQL previously defined, but you have to specify here how the map should appear.<br />
<br />
The contents of the R code box, are inserted into the mapfile in a LAYER block. Full documentation of what is permitted can be found in the [http://mapserver.org/mapfile/layer.html Mapserver documentation]<br />
<br />
Two sections are required (TYPE and CLASS) and there are some optional sections<br />
=====TYPE=====<br />
This can be POINT, LINE or POLYGON, depending on the map to be produced. For example, for a point map:<br />
TYPE POINT<br />
Other types can be used including CHART, CIRCLE, RASTER, but these are uncommon advanced features. <br />
<br />
=====CLASS=====<br />
This defines the appearance of the data, as well as the legend. A typical class block for a point map <br />
CLASS<br />
NAME "Kasus"<br />
STYLE<br />
SYMBOL "reddot"<br />
END # STYLE<br />
END # CLASS<br />
<br />
This will produce a layer with a single symbol (reddot) for all features, and a legend with 'Kasus'.<br />
<br />
For a polygon layer, you can define the colour of the outline and the fill:<br />
CLASS<br />
NAME "Pelatihan"<br />
STYLE<br />
COLOR 255 0 0<br />
OUTLINECOLOR 255 0 0<br />
SIZE 6<br />
END # STYLE<br />
END<br />
<br />
The style options are very powerful. See the [http://mapserver.org/mapfile/class.html#class Mapserver CLASS documentation] for more information.<br />
<br />
Standard SYMBOLs are pre-defined in a symbol file. For more symbols, this file will have to be manually edited.<br />
<br />
It is also possible to define multiple levels of shading, by referring to data from the query. For example:<br />
<br />
CLASS<br />
NAME "Belum gunakan"<br />
EXPRESSION ([laporan] = 0)<br />
STYLE<br />
COLOR 237 248 251<br />
END # STYLE<br />
END # CLASS<br />
<br />
CLASS<br />
NAME "1 - 5 laporan"<br />
EXPRESSION ([laporan] > 0 AND [laporan] < 6)<br />
STYLE<br />
COLOR 178 226 226<br />
END # STYLE<br />
END # CLASS<br />
<br />
CLASS<br />
NAME "6 - 50 laporan"<br />
EXPRESSION ([laporan] > 5 AND [laporan] < 50)<br />
STYLE<br />
COLOR 102 194 164<br />
END # STYLE<br />
END # CLASS<br />
<br />
CLASS<br />
NAME "> 50 laporan"<br />
EXPRESSION ([laporan] > 50)<br />
STYLE<br />
COLOR 35 139 69<br />
END # STYLE<br />
END # CLASS<br />
<br />
In this case, the query must have a field called "laporan" which has an integer (the number of reports submitted).<br />
<br />
The COLOR and OUTLINECOLOR lines require a RGB (red green blue) colour code. The [http://colorbrewer2.org/index.html ColorBrewer] web site is an excellent tool for picking good map colours and finding their RBG code.<br />
<br />
=====CLASSITEM=====<br />
This specifies that one field in the query will be used to determine the style of different features. For example:<br />
<br />
CLASSITEM "Hasil"<br />
CLASS<br />
NAME "Positif"<br />
EXPRESSION "Pos"<br />
STYLE<br />
SYMBOL "reddot"<br />
END<br />
END<br />
<br />
CLASS<br />
NAME "Negatif"<br />
EXPRESSION "Neg"<br />
STYLE<br />
SYMBOL "bluedot"<br />
END<br />
END<br />
<br />
This means that there must be a field in the query called "Hasil" and it will return values of either "Positif" or "Negatif"<br />
<br />
==Viewing maps==<br />
Menu root</div>Angushttp://wiki.isikhnas.com/index.php?title=Mapping&diff=33021Mapping2015-04-01T07:27:01Z<p>Angus: /* Mapfile code */</p>
<hr />
<div>=Mapping=<br />
The mapping system allows administrators to define new map-based reports rapidly through the interface, and for them to be viewed on-line.<br />
<br />
==Defining a new map==<br />
Maps are defined in the same way as other reports, using the Administration | Reports menu. There are two key differences compared to other reports: requirements for the SQL data definition, and style information (Mapfile code)<br />
<br />
===SQL===<br />
The SQL is similar to all other reports, and should be a single SELECT query. However, there are several particular requirements<br />
<br />
====Required fields====<br />
Every query must return two required fields:<br />
* gid - this is a 'geographic ID' and is a unique integer for each spatial unit returned. Often, this can just be the id from the locations table, but if there can be multiple reports per location, you need to choose another unique ID value. It doesn't matter which. If nothing else is available, you can also use the row number window function:<br />
select row_number() over () as gid, <br />
* the_geom: this is the spatial data and must be included in every report. It should always come from the projected version of the locations table spatial data. That is:<br />
** For polygon data (administrative units) this should be geom_proj (e.g. select geom_proj as the_geom, )<br />
** For point data (village locations etc) this should be centroid_proj (e.g. select centroid_proj as the_geom, )<br />
Don't use the standard geom and centroid columns, or the data will not be in the right projection and won't appear on the map.<br />
<br />
===Field names===<br />
Any fields generated in the query will be available to the user with a map query (where they click on a feature, and further information pops up). So that this feature works nicely, you should include all the data that a user might want to see, and name each field with a user-friendly name. For example<br />
SELECT<br />
sum(total) as "Julah hewan"<br />
<br />
===Mapfile code===<br />
The R code box of the Report definition interface is used to include mapfile code, which specifies the appearance of the output. <br />
<br />
Most of the mapfile is automatically generated using fixed standards and the SQL previously defined, but you have to specify here how the map should appear.<br />
<br />
The contents of the R code box, are inserted into the mapfile in a LAYER block. Full documentation of what is permitted can be found in the [[http://mapserver.org/mapfile/layer.html|Mapserver documentation]]<br />
<br />
Two sections are required (TYPE and CLASS) and there are some optional sections<br />
=====TYPE=====<br />
This can be POINT, LINE or POLYGON, depending on the map to be produced. For example, for a point map:<br />
TYPE POINT<br />
Other types can be used including CHART, CIRCLE, RASTER, but these are uncommon advanced features. <br />
<br />
=====CLASS=====<br />
This defines the appearance of the data, as well as the legend. A typical class block for a point map <br />
CLASS<br />
NAME "Kasus"<br />
STYLE<br />
SYMBOL "reddot"<br />
END # STYLE<br />
END # CLASS<br />
<br />
This will produce a layer with a single symbol (reddot) for all features, and a legend with 'Kasus'.<br />
<br />
For a polygon layer, you can define the colour of the outline and the fill:<br />
CLASS<br />
NAME "Pelatihan"<br />
STYLE<br />
COLOR 255 0 0<br />
OUTLINECOLOR 255 0 0<br />
SIZE 6<br />
END # STYLE<br />
END<br />
<br />
The style options are very powerful. See the [http://mapserver.org/mapfile/class.html#class|Mapserver CLASS documentation] for more information.<br />
<br />
Standard SYMBOLs are pre-defined in a symbol file. For more symbols, this file will have to be manually edited.<br />
<br />
It is also possible to define multiple levels of shading, by referring to data from the query. For example:<br />
<br />
CLASS<br />
NAME "Belum gunakan"<br />
EXPRESSION ([laporan] = 0)<br />
STYLE<br />
COLOR 237 248 251<br />
END # STYLE<br />
END # CLASS<br />
<br />
CLASS<br />
NAME "1 - 5 laporan"<br />
EXPRESSION ([laporan] > 0 AND [laporan] < 6)<br />
STYLE<br />
COLOR 178 226 226<br />
END # STYLE<br />
END # CLASS<br />
<br />
CLASS<br />
NAME "6 - 50 laporan"<br />
EXPRESSION ([laporan] > 5 AND [laporan] < 50)<br />
STYLE<br />
COLOR 102 194 164<br />
END # STYLE<br />
END # CLASS<br />
<br />
CLASS<br />
NAME "> 50 laporan"<br />
EXPRESSION ([laporan] > 50)<br />
STYLE<br />
COLOR 35 139 69<br />
END # STYLE<br />
END # CLASS<br />
<br />
In this case, the query must have a field called "laporan" which has an integer (the number of reports submitted).<br />
<br />
The COLOR and OUTLINECOLOR lines require a RGB (red green blue) colour code. The [http://colorbrewer2.org/index.html | ColorBrewer] web site is an excellent tool for picking good map colours and finding their RBG code.<br />
<br />
=====CLASSITEM=====<br />
This specifies that one field in the query will be used to determine the style of different features. For example:<br />
<br />
CLASSITEM "Hasil"<br />
CLASS<br />
NAME "Positif"<br />
EXPRESSION "Pos"<br />
STYLE<br />
SYMBOL "reddot"<br />
END<br />
END<br />
<br />
CLASS<br />
NAME "Negatif"<br />
EXPRESSION "Neg"<br />
STYLE<br />
SYMBOL "bluedot"<br />
END<br />
END<br />
<br />
This means that there must be a field in the query called "Hasil" and it will return values of either "Positif" or "Negatif"<br />
<br />
==Viewing maps==<br />
Menu root</div>Angushttp://wiki.isikhnas.com/index.php?title=Mapping&diff=33004Mapping2015-04-01T07:25:47Z<p>Angus: /* CLASS */</p>
<hr />
<div>=Mapping=<br />
The mapping system allows administrators to define new map-based reports rapidly through the interface, and for them to be viewed on-line.<br />
<br />
==Defining a new map==<br />
Maps are defined in the same way as other reports, using the Administration | Reports menu. There are two key differences compared to other reports: requirements for the SQL data definition, and style information (Mapfile code)<br />
<br />
===SQL===<br />
The SQL is similar to all other reports, and should be a single SELECT query. However, there are several particular requirements<br />
<br />
====Required fields====<br />
Every query must return two required fields:<br />
* gid - this is a 'geographic ID' and is a unique integer for each spatial unit returned. Often, this can just be the id from the locations table, but if there can be multiple reports per location, you need to choose another unique ID value. It doesn't matter which. If nothing else is available, you can also use the row number window function:<br />
select row_number() over () as gid, <br />
* the_geom: this is the spatial data and must be included in every report. It should always come from the projected version of the locations table spatial data. That is:<br />
** For polygon data (administrative units) this should be geom_proj (e.g. select geom_proj as the_geom, )<br />
** For point data (village locations etc) this should be centroid_proj (e.g. select centroid_proj as the_geom, )<br />
Don't use the standard geom and centroid columns, or the data will not be in the right projection and won't appear on the map.<br />
<br />
===Field names===<br />
Any fields generated in the query will be available to the user with a map query (where they click on a feature, and further information pops up). So that this feature works nicely, you should include all the data that a user might want to see, and name each field with a user-friendly name. For example<br />
SELECT<br />
sum(total) as "Julah hewan"<br />
<br />
===Mapfile code===<br />
The R code box of the Report definition interface is used to include mapfile code, which specifies the appearance of the output. <br />
<br />
Most of the mapfile is automatically generated using fixed standards and the SQL previously defined, but you have to specify here how the map should appear.<br />
<br />
The contents of the R code box, are inserted into the mapfile in a LAYER block. Full documentation of what is permitted can be found in the [[http://mapserver.org/mapfile/layer.html|Mapserver documentation]]<br />
<br />
Two sections are required (TYPE and CLASS) and there are some optional sections<br />
=====TYPE=====<br />
This can be POINT, LINE or POLYGON, depending on the map to be produced. For example, for a point map:<br />
TYPE POINT<br />
Other types can be used including CHART, CIRCLE, RASTER, but these are uncommon advanced features. <br />
<br />
=====CLASS=====<br />
This defines the appearance of the data, as well as the legend. A typical class block for a point map <br />
CLASS<br />
NAME "Kasus"<br />
STYLE<br />
SYMBOL "reddot"<br />
END # STYLE<br />
END # CLASS<br />
<br />
This will produce a layer with a single symbol (reddot) for all features, and a legend with 'Kasus'.<br />
<br />
For a polygon layer, you can define the colour of the outline and the fill:<br />
CLASS<br />
NAME "Pelatihan"<br />
STYLE<br />
COLOR 255 0 0<br />
OUTLINECOLOR 255 0 0<br />
SIZE 6<br />
END # STYLE<br />
END<br />
<br />
The style options are very powerful. See the [http://mapserver.org/mapfile/class.html#class|Mapserver CLASS documentation] for more information.<br />
<br />
Standard SYMBOLs are pre-defined in a symbol file. For more symbols, this file will have to be manually edited.<br />
<br />
It is also possible to define multiple levels of shading, by referring to data from the query. For example:<br />
<br />
CLASS<br />
NAME "Belum gunakan"<br />
EXPRESSION ([laporan] = 0)<br />
STYLE<br />
COLOR 237 248 251<br />
END # STYLE<br />
END # CLASS<br />
CLASS<br />
NAME "1 - 5 laporan"<br />
EXPRESSION ([laporan] > 0 AND [laporan] < 6)<br />
STYLE<br />
COLOR 178 226 226<br />
END # STYLE<br />
END # CLASS<br />
<br />
CLASS<br />
NAME "6 - 50 laporan"<br />
EXPRESSION ([laporan] > 5 AND [laporan] < 50)<br />
STYLE<br />
COLOR 102 194 164<br />
END # STYLE<br />
END # CLASS<br />
<br />
CLASS<br />
NAME "> 50 laporan"<br />
EXPRESSION ([laporan] > 50)<br />
STYLE<br />
COLOR 35 139 69<br />
END # STYLE<br />
END # CLASS<br />
<br />
In this case, the query must have a field called "laporan" which has an integer (the number of reports submitted).<br />
<br />
The COLOR and OUTLINECOLOR lines require a RGB (red green blue) colour code. The [http://colorbrewer2.org|ColorBrewer] web site is an excellent tool for picking good map colours and finding their RBG code.<br />
<br />
=====CLASSITEM=====<br />
This specifies that one field in the query will be used to determine the style of different features. For example:<br />
<br />
CLASSITEM "Hasil"<br />
CLASS<br />
NAME "Positif"<br />
EXPRESSION "Pos"<br />
STYLE<br />
SYMBOL "reddot"<br />
END<br />
END<br />
<br />
CLASS<br />
NAME "Negatif"<br />
EXPRESSION "Neg"<br />
STYLE<br />
SYMBOL "bluedot"<br />
END<br />
END<br />
<br />
This means that there must be a field in the query called "Hasil" and it will return values of either "Positif" or "Negatif"<br />
<br />
==Viewing maps==<br />
Menu root</div>Angushttp://wiki.isikhnas.com/index.php?title=Mapping&diff=33002Mapping2015-04-01T07:24:36Z<p>Angus: /* Mapfile code */</p>
<hr />
<div>=Mapping=<br />
The mapping system allows administrators to define new map-based reports rapidly through the interface, and for them to be viewed on-line.<br />
<br />
==Defining a new map==<br />
Maps are defined in the same way as other reports, using the Administration | Reports menu. There are two key differences compared to other reports: requirements for the SQL data definition, and style information (Mapfile code)<br />
<br />
===SQL===<br />
The SQL is similar to all other reports, and should be a single SELECT query. However, there are several particular requirements<br />
<br />
====Required fields====<br />
Every query must return two required fields:<br />
* gid - this is a 'geographic ID' and is a unique integer for each spatial unit returned. Often, this can just be the id from the locations table, but if there can be multiple reports per location, you need to choose another unique ID value. It doesn't matter which. If nothing else is available, you can also use the row number window function:<br />
select row_number() over () as gid, <br />
* the_geom: this is the spatial data and must be included in every report. It should always come from the projected version of the locations table spatial data. That is:<br />
** For polygon data (administrative units) this should be geom_proj (e.g. select geom_proj as the_geom, )<br />
** For point data (village locations etc) this should be centroid_proj (e.g. select centroid_proj as the_geom, )<br />
Don't use the standard geom and centroid columns, or the data will not be in the right projection and won't appear on the map.<br />
<br />
===Field names===<br />
Any fields generated in the query will be available to the user with a map query (where they click on a feature, and further information pops up). So that this feature works nicely, you should include all the data that a user might want to see, and name each field with a user-friendly name. For example<br />
SELECT<br />
sum(total) as "Julah hewan"<br />
<br />
===Mapfile code===<br />
The R code box of the Report definition interface is used to include mapfile code, which specifies the appearance of the output. <br />
<br />
Most of the mapfile is automatically generated using fixed standards and the SQL previously defined, but you have to specify here how the map should appear.<br />
<br />
The contents of the R code box, are inserted into the mapfile in a LAYER block. Full documentation of what is permitted can be found in the [[http://mapserver.org/mapfile/layer.html|Mapserver documentation]]<br />
<br />
Two sections are required (TYPE and CLASS) and there are some optional sections<br />
=====TYPE=====<br />
This can be POINT, LINE or POLYGON, depending on the map to be produced. For example, for a point map:<br />
TYPE POINT<br />
Other types can be used including CHART, CIRCLE, RASTER, but these are uncommon advanced features. <br />
<br />
=====CLASS=====<br />
This defines the appearance of the data, as well as the legend. A typical class block for a point map <br />
CLASS<br />
NAME "Kasus"<br />
STYLE<br />
SYMBOL "reddot"<br />
END # STYLE<br />
END # CLASS<br />
<br />
This will produce a layer with a single symbol (reddot) for all features, and a legend with 'Kasus'.<br />
<br />
For a polygon layer, you can define the colour of the outline and the fill:<br />
CLASS<br />
NAME "Pelatihan"<br />
STYLE<br />
COLOR 255 0 0<br />
OUTLINECOLOR 255 0 0<br />
SIZE 6<br />
END # STYLE<br />
END<br />
<br />
The style options are very powerful. See the [[http://mapserver.org/mapfile/class.html#class|Mapserver CLASS documentation]] for more information.<br />
<br />
Standard SYMBOLs are pre-defined in a symbol file. For more symbols, this file will have to be manually edited.<br />
<br />
It is also possible to define multiple levels of shading, by referring to data from the query. For example:<br />
<br />
CLASS<br />
NAME "Belum gunakan"<br />
EXPRESSION ([laporan] = 0)<br />
STYLE<br />
COLOR 237 248 251<br />
END # STYLE<br />
END # CLASS<br />
<br />
CLASS<br />
NAME "1 - 5 laporan"<br />
EXPRESSION ([laporan] > 0 AND [laporan] < 6)<br />
STYLE<br />
COLOR 178 226 226<br />
END # STYLE<br />
END # CLASS<br />
<br />
CLASS<br />
NAME "6 - 50 laporan"<br />
EXPRESSION ([laporan] > 5 AND [laporan] < 50)<br />
STYLE<br />
COLOR 102 194 164<br />
END # STYLE<br />
END # CLASS<br />
<br />
CLASS<br />
NAME "> 50 laporan"<br />
EXPRESSION ([laporan] > 50)<br />
STYLE<br />
COLOR 35 139 69<br />
END # STYLE<br />
END # CLASS<br />
<br />
In this case, the query must have a field called "laporan" which has an integer (the number of reports submitted).<br />
<br />
The COLOR and OUTLINECOLOR lines require a RGB (red green blue) colour code. The [[http://colorbrewer2.org/|ColorBrewer]] web site is an excellent tool for picking good map colours and finding their RBG code.<br />
<br />
<br />
=====CLASSITEM=====<br />
This specifies that one field in the query will be used to determine the style of different features. For example:<br />
<br />
CLASSITEM "Hasil"<br />
CLASS<br />
NAME "Positif"<br />
EXPRESSION "Pos"<br />
STYLE<br />
SYMBOL "reddot"<br />
END<br />
END<br />
<br />
CLASS<br />
NAME "Negatif"<br />
EXPRESSION "Neg"<br />
STYLE<br />
SYMBOL "bluedot"<br />
END<br />
END<br />
<br />
This means that there must be a field in the query called "Hasil" and it will return values of either "Positif" or "Negatif"<br />
<br />
==Viewing maps==<br />
Menu root</div>Angushttp://wiki.isikhnas.com/index.php?title=Mapping&diff=32998Mapping2015-04-01T07:02:18Z<p>Angus: Created page with "=Mapping= The mapping system allows administrators to define new map-based reports rapidly through the interface, and for them to be viewed on-line. ==Defining a new map== Ma..."</p>
<hr />
<div>=Mapping=<br />
The mapping system allows administrators to define new map-based reports rapidly through the interface, and for them to be viewed on-line.<br />
<br />
==Defining a new map==<br />
Maps are defined in the same way as other reports, using the Administration | Reports menu. There are two key differences compared to other reports: requirements for the SQL data definition, and style information (Mapfile code)<br />
<br />
===SQL===<br />
The SQL is similar to all other reports, and should be a single SELECT query. However, there are several particular requirements<br />
<br />
====Required fields====<br />
Every query must return two required fields:<br />
* gid - this is a 'geographic ID' and is a unique integer for each spatial unit returned. Often, this can just be the id from the locations table, but if there can be multiple reports per location, you need to choose another unique ID value. It doesn't matter which. If nothing else is available, you can also use the row number window function:<br />
select row_number() over () as gid, <br />
* the_geom: this is the spatial data and must be included in every report. It should always come from the projected version of the locations table spatial data. That is:<br />
** For polygon data (administrative units) this should be geom_proj (e.g. select geom_proj as the_geom, )<br />
** For point data (village locations etc) this should be centroid_proj (e.g. select centroid_proj as the_geom, )<br />
Don't use the standard geom and centroid columns, or the data will not be in the right projection and won't appear on the map.<br />
<br />
===Field names===<br />
Any fields generated in the query will be available to the user with a map query (where they click on a feature, and further information pops up). So that this feature works nicely, you should include all the data that a user might want to see, and name each field with a user-friendly name. For example<br />
SELECT<br />
sum(total) as "Julah hewan"<br />
<br />
===Mapfile code===<br />
<br />
<br />
==Viewing maps==<br />
Menu root</div>Angushttp://wiki.isikhnas.com/index.php?title=Technical_References&diff=32985Technical References2015-04-01T06:51:40Z<p>Angus: /* Web Site */</p>
<hr />
<div>=Technical references= <!--T:1--><br />
[[File:Troubleshooting.svg|80px|left]]<br />
<br />
==Overview== <!--T:2--><br />
[[Overview_of_data_managed|Overview of data managed]]<br />
<br />
==Database automated documentation== <!--T:3--><br />
[[iSIKHNAS code lists|Code lists]]<br />
<br />
<!--T:4--><br />
[[Database tables]] - Table listing<br />
<br />
[[Database functions]] - Function listing<br />
<br />
<!--T:5--><br />
[[SMS handler functions]] - Message handlers and business rules<br />
<br />
==Cloud server infrastructure== <!--T:6--><br />
These pages provide details on the AWS cloud server hosting and infrastructure.<br />
<br />
<!--T:7--><br />
[[Overview]]<br />
*[[IT:Servers|Servers]]<br />
*[[IT:Storage|Storage]]<br />
*[[IT:Queues|Queues]]<br />
<br />
==Guides and standards== <!--T:9--><br />
[[Image:Nuvola apps bookcase.png|130px|frameless|left]]<br />
<br />
=====Database===== <!--T:10--><br />
[[New table creation]] - Technical reference and standards<br />
<br />
=====SMS System===== <!--T:12--><br />
[[Modems]] - Modems and telephone numbers<br />
<br />
[[Adding a new modem]]<br />
<br />
<!--T:21--><br />
[[SMS server setup]] - Technical documentation<br />
<br />
<!--T:13--><br />
[[SMS handler setup]] - Technical documentation for setting up a new SMS handler<br />
<br />
<!--T:14--><br />
* [[SMS Handler: Step by step example]] - Example of steps required to create a new SMS handler<br />
<br />
<!--T:16--><br />
[[Manually sending individual or bulk SMS messages]]<br />
<br />
=====Web Site=====<br />
[[Advanced permissions|Manage advanced permissions]] - Give different users access to different pages<br />
<br />
=====Mapping=====<br />
[[Mapping|Mapping]] - Creating and editing map reports<br />
<br />
=====Standalone systems===== <!--T:17--><br />
[[ReportBot: automated viewing of website reports]]<br />
<br />
<!--T:18--><br />
[[InfoLab data export daemon]]<br />
<br />
==Wiki== <!--T:19--><br />
[[Using the wiki]]<br />
<br />
<!--T:20--><br />
[[Using Book Creator|Using Book Creator to download a copy of wiki in open document format]]</div>Angus