Finding and fixing vacant properties through crowdsourced data collection

March 26th, 2015 by Waylon Brunette

Shantanu Singh is the founder of Vacant Voices, an organization committed to solving the problem of abandoned homes in America's neighborhoods. In this guest post on Nafundi's blog, Shantanu explains how Vacant Voices uses ODK to collect and deliver crowd-sourced neighborhood data to community organizations who can make a difference. The full blog post is available here.

An excerpt of Shantanu blog post:

Vacant properties are an important issue that needs an urgent solution. A 2015 report concluded that 1 out of 4 foreclosures in the United States are vacant. The actual number at the end of January 2015 was over 142,000. The number is alarming when you consider the contagion and deleterious impact caused by vacant homes. Research has established that these blight-causing properties reduce property values, increase crime rates, and worsen physical and emotional health.

At Vacant Voices, we wanted to develop a tool to help these communities. One that would allow residents to collect data (e.g., a GPS tag for the location, a standardized description, and an optional image) of problem properties. The collection could be spontaneous or scheduled. Community-sourced data that we could deliver to decision makers was our goal.

Through prior experience, we understood municipal categorization of vacant properties to be technical and not uniform across the country – in short, not user friendly. At the same time, we knew geographic information systems (GIS) and government data already existed (the statistics above were extrapolated from federal and local data). However, these systems can be hard for communities to find, can be complicated to use, and use old data that may not even be relevant for the specific need.

To collect and analyze data sourced from the community, we needed a better way. After a lot of research, we came across ODK. It seemed too good to be true. In front of us, there was a solution, one that not only provided a checklist interface, it also organized the data into a database (no data entry!), and you could visualize the spatial relationship of properties on a map, along with performing analytics useful to decision makers. Now we could standardize the definition of a vacant home, in a rubric that eliminated subjectivity.

The full blog post is available here.

A map showing the concentration of homes with peeling paint. From this map, users can immediately see clusters of vacant properties which are priorities.



Open[fn] provides integration between ODK and Safesforce

March 13th, 2015 by Waylon Brunette

Over the years the ODK team has received numerous feature requests for integration between ODK tools and Fortunately, the team at Open[fn] has recently created a tool to make it easier for organizations to move data between different software platforms. While the Open[fn] platform is young it is launching with integrated ODK, SurveyCTO (company using ODK core technology), and support.

To try Open[fn] go to the website:

The Open[fn] platform's vision articulated in the Salesforce Foundation blog entry is:

"We see a future where the technical setup of a mobile money platform, a biometrics tool, even an offline clinic registration platform, feels just like downloading an app from the app store. We’re still a long way from that reality, but we’ve built a totally open-source integration platform that’s poised to bring together the “technology for development” landscape with clicks, not code. Our marketplace guides users to the right tools based on their needs, our blog will feature in-depth case studies and implementation guides, and our mapping tool allows non-technical users to get data flowing from one technology to another in a few minutes."

More information about the Open[fn] can be found on Salesforce Foundation blog entry or on their website

Sign-up/credentials video:
Create a mapping video:


Reducing errors and delays in collecting millions of World Food Programme data points

March 1st, 2015 by Waylon Brunette

Dennis Kinambuga is a Monitoring and Evaluation Officer with the African Economic Research Consortium (AERC), where he supports the monitoring and evaluation of the World Food Programme's Purchase for Progress project in 17 countries. In his guest post on Nafundi's blog, Dennis explains how Nafundi and ODK has helped AERC collect and analyze more than 3.6 million data points for the Purchase for Progress project.

Dennis Kinambuga writes:

The Purchase for Progress (P4P) project uses the World Food Programme's (WFP) purchasing power, paired with inventive local techniques and best practices, to bring smallholder farmers into formal value chains where they can earn more. The project started in 2008, and has improved the lives of hundreds of thousands of farmers in 20 countries in Africa, Asia, and Central America.

Collecting smallholder farmer data on paper is a nightmare

Monitoring and evaluation is key to proving P4P's efficacy and so the WFP collects longitudinal data on households and farmer organizations to monitor the project. In 2011, WFP partnered with the AERC to collect, clean, analyze, manage, and report on the quantitative data generated by 17 of the 20 P4P countries.

At the beginning of the project, the complex data sets, each with about 1,600 variables, were collected on paper. The data was then manually entered into computers at a later date. This paper-based process resulted in data collection errors, long delays before data entry, and difficulty in monitoring on-going surveys from AERC offices in Nairobi. It was a data management nightmare.

ODK reduced errors and delays in collecting millions of data points

In 2013, with the support of Nafundi, AERC started using ODK for data collection in Rwanda. The benefits were immediately clear. The time between data collection and analysis was reduced by almost half. Additionally, the near real time remote monitoring enabled catching and correcting errors while surveyors were still in the field.

Two WFP surveyors use ODK to collect data from a farmer organization in Rwanda.

AERC has since successfully used ODK to collect P4P data in Kenya, Ethiopia, El Salvador, Ghana, and Zambia. To date, more than 2,300 households and 230 farmer organizations have been surveyed using ODK in these countries. This represents more than 3.6 million data points collected with ODK.

With each deployment, there have been drastic reductions in the time between and effort required for data collection and analysis. We have also seen tremendous increases in data quality. For these reasons, AERC will continue to use ODK to collect and analyze data for monitoring and evaluation work at AERC.