Posts focused on Agriculture
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Can Nepal and Cambodia Really Have Common Agricultural Data Standards?
What does data-driven agricultural development in Nepal and Cambodia have in common? To answer this question, Development Gateway and partner Athena Infonomics are implementing the Accelerating Data-Driven Agriculture Development in Cambodia and Nepal Activity – funded by USAID and led by FHI360 through the mSTAR program – to support Feed the Future stakeholders in both countries improve their data interoperability and sharing practices.
Talking Agriculture Data Interoperability at ICTforAg 2018
Recently, we shared a post on how we’re driving progress towards inclusive agriculture data use by strengthening agriculture data interoperability through FHI360’s Mobile Solutions Technical Assistance and Research (mSTAR) project. If you’re interested in finding out more, join us on June 14th at the 2018 ICTforAg conference in Washington, D.C. We’re looking forward to connecting
What does Data Interoperability Require in Practice?
A few months ago, under the mSTAR project funded by USAID, DG and our partner Athena Infonomics (AI) set out to understand the underlying structure of the data currently being collected and managed by Feed the Future implementers, and how to best support them to open up and share their data through digital tools and best practices.
How Interoperability can Strengthen Agriculture and Nutrition
Food security, or people’s access to “sufficient, safe, and nutritious food,” remains a global challenge. Lack of access to nutritious food is not only more likely to affect those already facing difficulties such as poverty, economic shock and public health crises; when communities do not have adequate access to nutrition, they have a harder time
Location, Location, Location: A miniTAG on how project location data should be published and visualized through IATI
Subnational location information is repeatedly identified as critical for both donors and implementers to understand and learn from development activities around the world. “Information on who is doing what and where allows development organizations to maximize impact by finding gaps in funding, identifying partners and avoiding duplicative efforts.” However, confusion around how location data should