Many organizations in the developing world (e.g., NGOs), include digital data collection in their workflow. Data collected can include information that may be considered sensitive, such as medical or socioeconomic data, and which could be affected by computer security attacks or unintentional mishandling. This work, a collaboration between computer security and ICTD researchers, explores security and privacy attitudes, practices, and needs within organizations that use Open Data Kit (ODK), a prominent digital data collection platform. We conduct a detailed threat modeling exercise to inform our view on potential security threats, and then conduct and analyze a survey and interviews with technology experts in these organizations to ground this analysis in real deployment experiences. We then reflect upon our results, drawing lessons for both organizations collecting data and for tool developers.

This paper describes the design and implementation of Premise, a mobile-phone based platform for gathering reliable, quantitative data through on-the-ground networks of local contributors. Founded in 2012 and currently operating in 34 countries, Premise provides small incentives to ordinary citizens to collect high-quality data, and develops statistical algorithms to aggregate millions of individual contributions into reliable economic indicators. Our focus is on the deployment and scale-up of Premise's operations in Nigeria and Liberia, two contexts that highlight the diverse challenges involved in launching a crowd-based data collection platform, ranging from the recruitment and retention of motivated contributors, to the automatic detection of statistically aberrant data. The goals of this paper are thus twofold: first, to provide transparency into the operations of a new platform of growing prominence in the development community; and second, to highlight key lessons learned that can inform future design and deployment of novel methods for data collection and synthesis in developing economies.