A wide range of data challenges and issues face organizations working to monitor and achieve the Sustainable Development Goals. Some organizations work to improve development data in a particular sector or help build country capacity to produce and use these data. Others encounter data challenges as they work on other development issues. And some want to adapt their expertise to address development data issues but aren’t familiar with the data ecosystem or capacities of other organizations. National statistical offices and other data producers face a different set of challenges. How can they meet the monitoring and reporting demands of the SDGs? Should they adopt new methods of data collection and analysis? How reliable are citizen-generated data? Or big data estimates? And who are reliable partners? What are the gaps in the available data?

Our unique knowledge of development data allows us to support these organizations and help them overcome barriers and challenges. We serve as the technical data group for Data2X, supporting them through a several initiatives related to gender data. We also collaborate with many of our other partners on technical data issues.


The data value chain is a framework prepared for Data2X by Open Data Watch to help visualize the life cycle of data from collection to impact. It can serve as a management tool to monitor and evaluate the data production process or as a teaching tool to better recognize and understand the complex steps from data creation to use. The framework helps identify impediments to achieving data impacts and helps focus attention on areas of need. While the data value chain was motivated by research on collecting and documenting gender data impact stories, the concept applies to development data more broadly.

As the visualization below shows, the data value chain includes four major stages: collection, publication, uptake, and impact. These four stages are further separated into twelve steps: identify, collect, process, analyze, release, disseminate, connect, incentivize, influence, use, change, and reuse. Throughout the process, from one end of the value chain to another and back again, there should be constant feedback between producers and stakeholders. This visualization is free for anyone to use and reuse.

Our joint report with Data2X, The Data Value Chain: Production to Impact, provides an overview of the data value chain as a framework. It explains each of the stages and the steps within each one. The report also includes real-world examples of gender data that illustrate each stage of the data value chain.


The R2M Gender Data Query Tool, a joint product with Data2X, is an accompaniment to the Ready to Measure Phase II: Indicators Available to Monitor SDG Gender Targets. While measuring and monitoring the gender-related indicators in the Sustainable Development Goals (SDGs) may be difficult, this project shows that there is a solid starting-point. Using the data query tool, users can access data for 20 indicators to begin measuring gender equality for the SDGs. The tool is a result of compiling data from eight different international sources into one searchable database.