ODK Scan is designated Alpha software.
See Release Designations for the meaning of this designation.
The purpose of this documentation is describe what the ODK Scan is, what user documentation is available, and provide links to several presentations and reports on field deployments that use this tool.
Introduction to ODK Scan
1 Introduction to ODK Scan
ODK Scan is an Android application that uses the device’s camera and specialized code to automatically digitize written data from paper forms. Using the app, users take pictures of paper forms and ODK Scan detects and collects the fill-in bubble, checkbox, and written number data. It also saves image snippets of handwritten text and displays them on the screen for easy data entry. The digitized data can then be validated, exported, saved into a database, and used for custom data reports. This workflow from paper form to digital database occurs in five processes and is supported through the use of ODK suite tools.
2 Installing Scan
You must enable downloading from unknown sources by checking the checkbox beside Unknown sources on the Security screen of your Android device's Settings application.
Then, open your Android device's browser and download the rev 208 APK for ODK Scan v2.0 from here.
You should then be able to install that APK onto your device by choosing the Android Notification of the completion of the download. On some devices, you may need to open a file manager and double-tap on the downloaded file in the Downloads directory to trigger the install. On others, you may need to rename the file in the Downloads directory to end with .apk before double-tapping it to trigger the install.
Device requirements. ODK Scan is designed for use on an Android device version 4.4 or newer, though 6.0 and above are not yet fully supported.
In addition to ODK Scan, you must have the rev 206 APKs for the following installed on your phone:
To synchronize your data with the cloud you will also need an Aggregate v1.4.12 instance:
ODK Suitcase provides a convenient way to download your aggregated data to your desktop as a csv, which can be used in your overall data workflow:
Before scanning you'll first need to create printable form template using the Scan Form Designer. The Scan Form Designer lives in the Application Desginer:
3 Documentation Links
Below are links to further information and step-by-step guides to assist you at each stage of the ODK Scan workflow.
4 Digitizing Paper and ODK Scan in the Field: Presentations and Reports
VillageReach, ODK Scan Field Test: Malawi Community Health Worker Register Final Field Test Report. Dec 4, 2015.
Paper-Digital-Workflows-in-Global-Development-Organizations, Nicola Dell, Trevor Perrier, Neha Kumar, Mitchell Lee, Rachel Powers, Gaetano Borriello (2015).
- Abstract: Global development organizations rely on the essential affordances provided by both paper and digital materials to navigate hurdles posed by poor infrastructure, low connectivity, linguistic differences, and other socioeconomic constraints that render communication and collaboration challenging. This paper examines the collaborative practices around paper-digital workflows within global development organizations operating in low-resource environments. We use a mixed methods approach to gather data from 23 organizations in 16 countries.Our findings show the tensions that arise between the ubiquitousness of paper and the desirability of digitized data, and highlight the challenges associated with transitioning information several times between paper and digital materials. We also reveal design opportunities for new tools to bridge the gap between paper-based and digital information in low-resource settings. Finally, we contribute a nuanced understanding of the cross-cultural and infrastructural challenges that influence the paper-digital lifecycle. Our findings will be useful for researchers and practitioners interested in understanding for researchers and practitioners interested in understanding or participating in the workflows that drive global development.
VillageReach. ODK Scan Recommendation Report_FINAL White Paper. April 2015.
Integrating-ODK-Scan-into-the-CHW-Supply-Chain-in-Mozambique, Nicola Dell, Jessica Crawford, Nathan Breit, Timóteo Chaluco, Aida Coelho, Joseph McCord, and Gaetano Borriello (2013).
- Abstract: We describe our experiences integrating ODK Scan into the community health worker (CHW) supply chain in Mozambique. ODK Scan is a mobile application that uses computer vision techniques to digitize data from paper forms. The application automatically classifies machine-readable data types, like bubbles and checkboxes, and assists users with the manual entry of handwritten text and numbers. We designed an intervention that uses paper forms in conjunction with ODK Scan to monitor CHW usage of essential health commodities, finding that the application is capable of providing supervisors and stakeholders with important information regarding health commodity availability in the field. Specifically, we (1) detail our experiences integrating ODK Scan into the health worker supply chain in Mozambique, with particular emphasis on the critical (and often under-reported) role of practitioners; (2) evaluate the impact of the technology at multiple levels of the information hierarchy, providing quantitative and qualitative data that exposes the benefits, challenges and limitations of the technology; and (3) share lessons learned and provide actionable guidance to researchers and practitioners interested in ODK Scan or other systems that bridge the gap between paper-based and digital data collection.
Digitizing Paper Forms with Mobile Imaging Technologies, Nicola Dell, Nathan Breit, Timóteo Chaluco, Jessica Crawford, Gaetano Borriello (2012).
- Abstract: In low-resource settings in developing countries, most records are still captured and maintained using paper forms. Despite a recent proliferation of digital data collection systems, paper forms remain a trusted, low-cost and ubiquitous medium that will continue to be utilized in these communities for years to come. However, it can be challenging to aggregate, share, and analyze the data collected using paper forms. This paper presents mScan, a mobile smartphone application that uses computer vision to capture data from paper forms that use a multiple choice or bubble format. The initial mScan implementation targets the task of digitizing paper forms used to record vaccine statistics in rural health centers in Mozambique. We have evaluated the accuracy and performance of mScan under a variety of different environmental conditions, and our results show that mScan is a robust tool that is capable of accurately capturing and digitizing data from paper forms.