More food security data than ever is being generated by technologies and agencies. To bring order to the ‘mess’ its data had become, the World Food Programme took an open approach – paving the way to bring information to hard-to-reach communities
Humanitarian aid being delivered to remote Sierra Leonean islands, which were restricted with re-supply during the Ebola outbreak on the mainland. CC BY 2.0, uploaded by PRODefence Images.
When a natural or man-made disaster strikes, humanitarian responders need numbers about its impact in order to advocate and plan for an effective response. Reaching out to communities helps agencies understand how people have been affected, how they are coping and what assistance they need. The food security data landscape is complex: new technologies mean that more data than ever is collected by a mosaic of agencies.
The World Food Programme’s Food Security Analysis Unit is one of many groups engaged in such assessment work and data collection. In this piece we outline how we have approached data management in the information era, and the challenges we see ahead.
What really pushed us to ‘go open’ with our data? We recently started to collect data remotely through mobiles. We usually ask people what types of foods they have been consuming and what coping strategies they use to make ends meet. Our mobile VAM project – initially funded by the Humanitarian Innovation Fund – involves using SMS, ‘robocalls’ (where people respond to recorded audio messages) and operators to call people on phones they already have. Since no expensive smartphones or data plans are required, we can collect data quickly and safely, with minimal expense, leading us to source more information from more places than ever before.
We collected over 100,000 questionnaires using this method in 2015, a seven-fold increase from the previous year. However, while mobile data collection proved to be an effective way to collect a lot of data, it raised tremendous challenges that an open data approach helped solve.
Reality struck during the Ebola emergency in 2014. When we deployed mVAM for the Ebola response, we soon found ourselves drowning in a deluge of incoming SMS data and facing a steady stream of requests from partners who wanted access to our information in order to plan their responses. The emails and phone calls were piling up, and soon we found ourselves tangled in a web of Excel files and PDF reports. We desperately needed a way to put some order into the mess we had created, so we invested in systems that enabled us to adopt open data.
Here’s what we set up:
As the workflow shows, our survey data comes directly from respondents who take an SMS, IVR or voice survey. This data is then stored in a centralised open databank that covers the main indicators we use to measure food security in a database with a standardised schema. The most common indicators we use are the Food Consumption Score, the Coping Strategies Index and a measure of sentiment in the open-ended question our surveys include. We also collect data about food prices.
We are careful to protect people’s identities; respondents’ phone numbers are encrypted and never shared, and only aggregated data is shared on an open-access basis.