Reimagining Development Data (RD²)
AidData
Academia
Global
The goal of AidData’s Reimagining Development (RD²) data project is to help each sector achieve its high-level objectives by supporting the production of data assets in resource-constrained environments, promoting approaches that remain resilient during short-term financial fluctuations, breaking down the silos of development data as ends unto themselves, and ensuring the sustainability of data resources over the long term. RD² will achieve this goal by providing information on the data ecosystem to donors and data producers, and by facilitating collaboration among those stakeholders.
Toward this end, our project has 8 key objectives:
- Establishing an inventory of key data assets (by country, year, sector, and region)
- Determining the funding trends for data assets (by funder, country, year, sector, and region)
- Learning about the priorities for data assets (by stakeholder group, sector, region, producers vs. users, and Global South vs. Global North)
- Assessing use patterns of data assets (by stakeholder group, country, year, sector, and region)
- Determining ways to make data assets more sustainable (by data asset, country, region, and level of development)
- Assessing the capacity of countries in the Global South to design, produce, and maintain data assets
- Promoting collaboration between stakeholders on the design, production, and maintenance of key data assets
- Informing funders and policy makers about the levels and types of support needed to ensure the production and maintenance of data assets
Over the past several decades, data systems have played a crucial role in tracking and responding to poverty, diseases, deforestation, food shortages, natural disasters, and more. Data has saved and improved lives. It is relied upon not only by aid agencies but also by governments and civil society who are often working on the front lines.
But many of the world’s established data systems are now facing their own life-and-death struggle in the wake of unexpected funding cuts. AidData’s Reimagining Development Data (RD²) project seeks to assess the landscape of data systems to see where the impact of diminished core financial support is the most dire.
We also seek to identify opportunities to learn and improve at this juncture. Many of the challenges in the data ecosystem are not new. Rather, these are persistent issues impacting data production, use, and ownership. As development stakeholders seek to rebuild a data landscape, how can we reimagine a better status quo?
AidData will conduct activities for RD² across three main components, which interact and have substantial overlap in period of implementation. The first component will assess the landscape of related projects; perform a global inventory of key data assets; conduct a systematic review of the funding, coverage, uptake, and sustainability of these assets; and develop a dashboard presenting results of the systematic review. In the second component, AidData will design and implement a global survey of data asset producers and users, conduct key informant interviews (KIIs), and produce policy briefs for the five sectors, as well as a synthesis report combining the findings from the systematic review, survey, and KIIs. The third component consists of AidData hosting remote briefings across five sectors and two regional convenings for donors, data producers, and data users in both the Global South and Global North.
We will monitor progress on the Reimagining Development Data project at two levels. The first, directly quantifiable level will be in the uptake of our findings and recommendations by key stakeholders in the data landscape. This will include use by funders to identify and support highly vulnerable data sources, as well as use by country partners in charting paths to more resilient data processes, among others. At multiple points in the project timeline, AidData will publish findings emerging from the different components of the research and identify opportunities for partner engagement.
The second level, less directly quantifiable but with a great potential for transformational change, will be in the connections and communities of practice developed through the data convenings. The convenings intend to foster new connections between organizations to chart their own paths forward, and will continue to generate change after the end of the formal RD² project period.