SlideShare une entreprise Scribd logo
1  sur  24
BY :
LISSY VERMA
SHRADDHA GUPTA
   Data Collection
     ODK : Open Data Kit
     Demo
   Usher : Improving Data Quality
     Purpose
     Implementation
     Results
   Data collection in developing areas is
    difficult.

   None of existing tools suffice.

   Based on need, new features are needed.
   ODK is a tool suite for collection and
    management of data on mobile phones.

   The main objective is to provide open
    source tools.
   ODK COLLECT
     Collects Data

   ODK AGGREGATE
     Store Data, view and export.

   ODK MANAGE
     Remote Device Management
   AMPATH deployed the ODK for data
    collection for medical purpose.

   Deployment was found to be successful
    minimizing delays and improving lives of
    healthcare workers and other people.
   Expertise in form design
   Double Entry : Costly
   Data Cleaning
Constraints
   Combo-boxes.


Reduce Time
   Automatically filled Leave-forms.
ESCORTER : Guide towards correct entries.

 Question Ordering in form.

  Greedy Information Gain

 Dynamically Reorder Questions

 Predict Errors to Re-ask.

  Contextualized Error Likelihood Principle.
   Concept : An unscrupulous door-to-door surveyor Shirks

    Work, ask only important questions.

     Greedy Information Gain

   Uniform Prior : Equal likely inputs
       Training Set

   Context – specific Model Required

   Bayesian Learning
   The patient dataset collected at a rural
    HIV/AIDS clinic at Tanzania.

   Survey dataset, responses from 1986 poll
    about race and politics
Bayesian Network for the patient dataset
Question layout generated by the algorithm
Approximates Double Entry

   Uncertainty : High Entropy

   Outliers
   Due to digital divide between the developing and
    developed areas, it is very difficult to collect and use data
    in the developing regions.
   The main problems being :
    Lack of reliable infrastructure,
    Proper connectivity, and,
    Inadequate expertise.
   Currently available tools for data collection like Pedragon
    Forms, Nokia Data Gathering, Java-Rosa, RapidSMS etc.
    are difficult to deploy, hard to use, complicated to scale
    and rarely customizable.
 The Open Data Kit or simply ODK is a suite of tools for data collection that
  uses Google’s Android platform.
 The main objectives of the technology are :
  Modularising and customising tools
  Use of open interfaces and standards
  Long time survival of tools.
 The three components of ODK are:
  1. ODK Collect : collects data using Forms.
  2. ODK Aggregate : ready to deploy online repository to store, view and export
  collected data.
  3. ODK Build : enables users to generate forms.
  4. ODK Voice : maps Forms to sound snippets.
  5. ODK Clinic : mobile medical record system.
  6. ODK Manage : maintains database of all phones for remote device
  management
  7. ODK Validate : validates Form.
  Other tools being ODK Dropbox, ODK Rangefinder, ODK Tasks, ODK Listen
  and ODK Visualise.

Contenu connexe

Tendances

Workshop using open source software for mobile data collection workshop - a...
Workshop   using open source software for mobile data collection workshop - a...Workshop   using open source software for mobile data collection workshop - a...
Workshop using open source software for mobile data collection workshop - a...
Wisconsin Land Information Association
 
Enabling digital transformation api ecosystems and data virtualization
Enabling digital transformation   api ecosystems and data virtualizationEnabling digital transformation   api ecosystems and data virtualization
Enabling digital transformation api ecosystems and data virtualization
Denodo
 
MLUC 2011 XQuery Enigma
MLUC 2011 XQuery EnigmaMLUC 2011 XQuery Enigma
MLUC 2011 XQuery Enigma
Peter O'Kelly
 
Encompassing Information Integration
Encompassing Information IntegrationEncompassing Information Integration
Encompassing Information Integration
nguyenfilip
 
Information Technology
Information TechnologyInformation Technology
Information Technology
Sahil Mahajan
 

Tendances (20)

Workshop using open source software for mobile data collection workshop - a...
Workshop   using open source software for mobile data collection workshop - a...Workshop   using open source software for mobile data collection workshop - a...
Workshop using open source software for mobile data collection workshop - a...
 
Open Data Kit
Open Data KitOpen Data Kit
Open Data Kit
 
Introduction to odk
Introduction to odkIntroduction to odk
Introduction to odk
 
Odk getting started
Odk getting startedOdk getting started
Odk getting started
 
Mobile Offline First for inclusive data that spans the data divide
Mobile Offline First for inclusive data that spans the data divideMobile Offline First for inclusive data that spans the data divide
Mobile Offline First for inclusive data that spans the data divide
 
Training on Develop Mobile Data Collection Solutions using Kobo Toolbox
Training on Develop Mobile Data Collection Solutions using Kobo ToolboxTraining on Develop Mobile Data Collection Solutions using Kobo Toolbox
Training on Develop Mobile Data Collection Solutions using Kobo Toolbox
 
Data Virtualization and ETL
Data Virtualization and ETLData Virtualization and ETL
Data Virtualization and ETL
 
Jboss Teiid - The data you have on the place you need
Jboss Teiid - The data you have on the place you needJboss Teiid - The data you have on the place you need
Jboss Teiid - The data you have on the place you need
 
Big data analytic platform
Big data analytic platformBig data analytic platform
Big data analytic platform
 
Enabling digital transformation api ecosystems and data virtualization
Enabling digital transformation   api ecosystems and data virtualizationEnabling digital transformation   api ecosystems and data virtualization
Enabling digital transformation api ecosystems and data virtualization
 
FOSS Sea 2014_DataWarehouse & BigData_Владимир Слободянюк ( Luxoft)
FOSS Sea 2014_DataWarehouse & BigData_Владимир Слободянюк ( Luxoft)FOSS Sea 2014_DataWarehouse & BigData_Владимир Слободянюк ( Luxoft)
FOSS Sea 2014_DataWarehouse & BigData_Владимир Слободянюк ( Luxoft)
 
Beyond the Data Lake - Matthias Korn, Technical Consultant at Data Virtuality
Beyond the Data Lake - Matthias Korn, Technical Consultant at Data VirtualityBeyond the Data Lake - Matthias Korn, Technical Consultant at Data Virtuality
Beyond the Data Lake - Matthias Korn, Technical Consultant at Data Virtuality
 
Data Virtualization to Survive a Multi and Hybrid Cloud World
Data Virtualization to Survive a Multi and Hybrid Cloud WorldData Virtualization to Survive a Multi and Hybrid Cloud World
Data Virtualization to Survive a Multi and Hybrid Cloud World
 
Sap webi chart creation from table
Sap webi chart creation from tableSap webi chart creation from table
Sap webi chart creation from table
 
MLUC 2011 XQuery Enigma
MLUC 2011 XQuery EnigmaMLUC 2011 XQuery Enigma
MLUC 2011 XQuery Enigma
 
Presentation on BCS Database Products January 2011
Presentation on BCS Database Products   January 2011Presentation on BCS Database Products   January 2011
Presentation on BCS Database Products January 2011
 
The Data Web and PLM
The Data Web and PLMThe Data Web and PLM
The Data Web and PLM
 
Encompassing Information Integration
Encompassing Information IntegrationEncompassing Information Integration
Encompassing Information Integration
 
Information Technology
Information TechnologyInformation Technology
Information Technology
 
The Curse of the Data Lake Monster
The Curse of the Data Lake MonsterThe Curse of the Data Lake Monster
The Curse of the Data Lake Monster
 

En vedette

PresentationFinal
PresentationFinalPresentationFinal
PresentationFinal
Lin Han
 
FluxGraph: a time-machine for your graphs
FluxGraph: a time-machine for your graphsFluxGraph: a time-machine for your graphs
FluxGraph: a time-machine for your graphs
datablend
 
Clinical Data Management
Clinical Data ManagementClinical Data Management
Clinical Data Management
biinoida
 

En vedette (20)

Visual Exploration of Clinical and Genomic Data for Patient Stratification
Visual Exploration of Clinical and Genomic Data for Patient StratificationVisual Exploration of Clinical and Genomic Data for Patient Stratification
Visual Exploration of Clinical and Genomic Data for Patient Stratification
 
Malmo 11.11.2008
Malmo 11.11.2008Malmo 11.11.2008
Malmo 11.11.2008
 
Cancer Research Data Ecosystem - Dr. Warren Kibbe
Cancer Research Data Ecosystem - Dr. Warren KibbeCancer Research Data Ecosystem - Dr. Warren Kibbe
Cancer Research Data Ecosystem - Dr. Warren Kibbe
 
PresentationFinal
PresentationFinalPresentationFinal
PresentationFinal
 
how to sell
how to sellhow to sell
how to sell
 
Linked Cancer Genome Atlas Database
Linked Cancer Genome Atlas DatabaseLinked Cancer Genome Atlas Database
Linked Cancer Genome Atlas Database
 
LSQ: The Linked SPARQL Queries Dataset
LSQ: The Linked SPARQL Queries DatasetLSQ: The Linked SPARQL Queries Dataset
LSQ: The Linked SPARQL Queries Dataset
 
Clinical research training - Dr Blanaid Mee - Dec 7th 2016
Clinical research training - Dr Blanaid Mee - Dec 7th 2016Clinical research training - Dr Blanaid Mee - Dec 7th 2016
Clinical research training - Dr Blanaid Mee - Dec 7th 2016
 
City of hope research informatics common data elements
City of hope research informatics common data elementsCity of hope research informatics common data elements
City of hope research informatics common data elements
 
Patient profiling disaggregating the data
Patient profiling disaggregating the dataPatient profiling disaggregating the data
Patient profiling disaggregating the data
 
Patient-Generated Data for Cancer Treatment and Management
Patient-Generated Data for Cancer Treatment and ManagementPatient-Generated Data for Cancer Treatment and Management
Patient-Generated Data for Cancer Treatment and Management
 
FluxGraph: a time-machine for your graphs
FluxGraph: a time-machine for your graphsFluxGraph: a time-machine for your graphs
FluxGraph: a time-machine for your graphs
 
iHT² Health IT Summit New York - Cancer Care Ontario Presentation "Transformi...
iHT² Health IT Summit New York - Cancer Care Ontario Presentation "Transformi...iHT² Health IT Summit New York - Cancer Care Ontario Presentation "Transformi...
iHT² Health IT Summit New York - Cancer Care Ontario Presentation "Transformi...
 
Impact of Multidisciplinary Discussion on Treatment Outcome For Gynecologic C...
Impact of Multidisciplinary Discussion on Treatment Outcome For Gynecologic C...Impact of Multidisciplinary Discussion on Treatment Outcome For Gynecologic C...
Impact of Multidisciplinary Discussion on Treatment Outcome For Gynecologic C...
 
Elective Care Conference: the role of the MDT coordinator role
Elective Care Conference: the role of the MDT coordinator role Elective Care Conference: the role of the MDT coordinator role
Elective Care Conference: the role of the MDT coordinator role
 
2015 Micromedex使用者大會 如何在臨床工作中找到實證解答
2015 Micromedex使用者大會 如何在臨床工作中找到實證解答2015 Micromedex使用者大會 如何在臨床工作中找到實證解答
2015 Micromedex使用者大會 如何在臨床工作中找到實證解答
 
National Cancer Data Ecosystem and Data Sharing
National Cancer Data Ecosystem and Data SharingNational Cancer Data Ecosystem and Data Sharing
National Cancer Data Ecosystem and Data Sharing
 
Swedish National Board of Health and Welfare Mona Heurgren
Swedish National Board of Health and Welfare Mona Heurgren Swedish National Board of Health and Welfare Mona Heurgren
Swedish National Board of Health and Welfare Mona Heurgren
 
Clinical Data Repository vs. A Data Warehouse - Which Do You Need?
Clinical Data Repository vs. A Data Warehouse - Which Do You Need?Clinical Data Repository vs. A Data Warehouse - Which Do You Need?
Clinical Data Repository vs. A Data Warehouse - Which Do You Need?
 
Clinical Data Management
Clinical Data ManagementClinical Data Management
Clinical Data Management
 

Similaire à Data collection

Similaire à Data collection (20)

Advanced Analytics and Machine Learning with Data Virtualization
Advanced Analytics and Machine Learning with Data VirtualizationAdvanced Analytics and Machine Learning with Data Virtualization
Advanced Analytics and Machine Learning with Data Virtualization
 
Lecture # 9.pptx
Lecture # 9.pptxLecture # 9.pptx
Lecture # 9.pptx
 
Data Science- Basics.pptx
Data Science- Basics.pptxData Science- Basics.pptx
Data Science- Basics.pptx
 
Innovation med big data – chr. hansens erfaringer
Innovation med big data – chr. hansens erfaringerInnovation med big data – chr. hansens erfaringer
Innovation med big data – chr. hansens erfaringer
 
Ch1IntroductiontoDataScience.pptx
Ch1IntroductiontoDataScience.pptxCh1IntroductiontoDataScience.pptx
Ch1IntroductiontoDataScience.pptx
 
Lesson 1 introduction to_big_data_and_hadoop.pptx
Lesson 1 introduction to_big_data_and_hadoop.pptxLesson 1 introduction to_big_data_and_hadoop.pptx
Lesson 1 introduction to_big_data_and_hadoop.pptx
 
Delivering Faster Insights with a Logical Data Fabric
Delivering Faster Insights with a Logical Data FabricDelivering Faster Insights with a Logical Data Fabric
Delivering Faster Insights with a Logical Data Fabric
 
Department of Commerce App Challenge: Big Data Dashboards
Department of Commerce App Challenge: Big Data DashboardsDepartment of Commerce App Challenge: Big Data Dashboards
Department of Commerce App Challenge: Big Data Dashboards
 
Data management plans – EUDAT Best practices and case study | www.eudat.eu
Data management plans – EUDAT Best practices and case study | www.eudat.euData management plans – EUDAT Best practices and case study | www.eudat.eu
Data management plans – EUDAT Best practices and case study | www.eudat.eu
 
Uniting traditional GIS and mainstream IT
Uniting traditional GIS and mainstream ITUniting traditional GIS and mainstream IT
Uniting traditional GIS and mainstream IT
 
Building an Open Source Staff-Facing Tablet App for Library Assessment
Building an Open Source Staff-Facing Tablet App for Library AssessmentBuilding an Open Source Staff-Facing Tablet App for Library Assessment
Building an Open Source Staff-Facing Tablet App for Library Assessment
 
Quicker Insights and Sustainable Business Agility Powered By Data Virtualizat...
Quicker Insights and Sustainable Business Agility Powered By Data Virtualizat...Quicker Insights and Sustainable Business Agility Powered By Data Virtualizat...
Quicker Insights and Sustainable Business Agility Powered By Data Virtualizat...
 
An Overview of BigData
An Overview of BigDataAn Overview of BigData
An Overview of BigData
 
2007 REVISED-ACGME-Poster
2007 REVISED-ACGME-Poster2007 REVISED-ACGME-Poster
2007 REVISED-ACGME-Poster
 
Big Data Tutorial For Beginners | What Is Big Data | Big Data Tutorial | Hado...
Big Data Tutorial For Beginners | What Is Big Data | Big Data Tutorial | Hado...Big Data Tutorial For Beginners | What Is Big Data | Big Data Tutorial | Hado...
Big Data Tutorial For Beginners | What Is Big Data | Big Data Tutorial | Hado...
 
Unlocking New Insights with Information Discovery
Unlocking New Insights with Information DiscoveryUnlocking New Insights with Information Discovery
Unlocking New Insights with Information Discovery
 
Infopulse AI, Data Science & RPA Managed Services
Infopulse AI, Data Science & RPA Managed ServicesInfopulse AI, Data Science & RPA Managed Services
Infopulse AI, Data Science & RPA Managed Services
 
Big Data-Survey
Big Data-SurveyBig Data-Survey
Big Data-Survey
 
Presentation1
Presentation1Presentation1
Presentation1
 
HIGH SPEED DATA RETRIEVAL FROM NATIONAL DATA CENTER (NDC) REDUCING TIME AND ...
 HIGH SPEED DATA RETRIEVAL FROM NATIONAL DATA CENTER (NDC) REDUCING TIME AND ... HIGH SPEED DATA RETRIEVAL FROM NATIONAL DATA CENTER (NDC) REDUCING TIME AND ...
HIGH SPEED DATA RETRIEVAL FROM NATIONAL DATA CENTER (NDC) REDUCING TIME AND ...
 

Dernier

+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
?#DUbAI#??##{{(☎️+971_581248768%)**%*]'#abortion pills for sale in dubai@
 

Dernier (20)

TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
 
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
 
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost SavingRepurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
 
Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024
 
Real Time Object Detection Using Open CV
Real Time Object Detection Using Open CVReal Time Object Detection Using Open CV
Real Time Object Detection Using Open CV
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Script
 
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...
 
Strategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a FresherStrategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a Fresher
 
Apidays Singapore 2024 - Scalable LLM APIs for AI and Generative AI Applicati...
Apidays Singapore 2024 - Scalable LLM APIs for AI and Generative AI Applicati...Apidays Singapore 2024 - Scalable LLM APIs for AI and Generative AI Applicati...
Apidays Singapore 2024 - Scalable LLM APIs for AI and Generative AI Applicati...
 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
 
presentation ICT roal in 21st century education
presentation ICT roal in 21st century educationpresentation ICT roal in 21st century education
presentation ICT roal in 21st century education
 
Ransomware_Q4_2023. The report. [EN].pdf
Ransomware_Q4_2023. The report. [EN].pdfRansomware_Q4_2023. The report. [EN].pdf
Ransomware_Q4_2023. The report. [EN].pdf
 
Corporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptxCorporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptx
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt Robison
 
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
 
DBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor PresentationDBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor Presentation
 
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
 
Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)
 

Data collection

  • 2. Data Collection  ODK : Open Data Kit  Demo  Usher : Improving Data Quality  Purpose  Implementation  Results
  • 3. Data collection in developing areas is difficult.  None of existing tools suffice.  Based on need, new features are needed.
  • 4. ODK is a tool suite for collection and management of data on mobile phones.  The main objective is to provide open source tools.
  • 5. ODK COLLECT  Collects Data  ODK AGGREGATE  Store Data, view and export.  ODK MANAGE  Remote Device Management
  • 6.
  • 7. AMPATH deployed the ODK for data collection for medical purpose.  Deployment was found to be successful minimizing delays and improving lives of healthcare workers and other people.
  • 8. Expertise in form design  Double Entry : Costly  Data Cleaning
  • 9. Constraints  Combo-boxes. Reduce Time  Automatically filled Leave-forms.
  • 10. ESCORTER : Guide towards correct entries.  Question Ordering in form.  Greedy Information Gain  Dynamically Reorder Questions  Predict Errors to Re-ask.  Contextualized Error Likelihood Principle.
  • 11. Concept : An unscrupulous door-to-door surveyor Shirks Work, ask only important questions.  Greedy Information Gain  Uniform Prior : Equal likely inputs  Training Set  Context – specific Model Required  Bayesian Learning
  • 12. The patient dataset collected at a rural HIV/AIDS clinic at Tanzania.  Survey dataset, responses from 1986 poll about race and politics
  • 13. Bayesian Network for the patient dataset
  • 14. Question layout generated by the algorithm
  • 15. Approximates Double Entry  Uncertainty : High Entropy  Outliers
  • 16.
  • 17.
  • 18.
  • 19.
  • 20.
  • 21.
  • 22.
  • 23. Due to digital divide between the developing and developed areas, it is very difficult to collect and use data in the developing regions.  The main problems being : Lack of reliable infrastructure, Proper connectivity, and, Inadequate expertise.  Currently available tools for data collection like Pedragon Forms, Nokia Data Gathering, Java-Rosa, RapidSMS etc. are difficult to deploy, hard to use, complicated to scale and rarely customizable.
  • 24.  The Open Data Kit or simply ODK is a suite of tools for data collection that uses Google’s Android platform.  The main objectives of the technology are : Modularising and customising tools Use of open interfaces and standards Long time survival of tools.  The three components of ODK are: 1. ODK Collect : collects data using Forms. 2. ODK Aggregate : ready to deploy online repository to store, view and export collected data. 3. ODK Build : enables users to generate forms. 4. ODK Voice : maps Forms to sound snippets. 5. ODK Clinic : mobile medical record system. 6. ODK Manage : maintains database of all phones for remote device management 7. ODK Validate : validates Form. Other tools being ODK Dropbox, ODK Rangefinder, ODK Tasks, ODK Listen and ODK Visualise.