Data kitchens – putting users at the centre of development solutions

As the 53rd session of the UN Statistical commission came to a close, I was left with two related questions: is the data community fulfilling its commitment to put data users at the centre of solutions? And if it is, whose data should we prioritise to achieve the objectives of the Cape Town Global Action Plan for Sustainable Development Data [PDF]?

National statistical offices are facing an unprecedented demand for real-time information on people and their needs, not only from policymakers, but also from citizens trying to make their voices heard , who sit outside the traditional notion of the ‘data community.’ However, the most vulnerable people remain the most likely to be missing from national statistics, and global datasets remain unfit for targeted responses at the local level.

Barriers to better data use

DI is a longstanding champion of data use. Our 2018 ‘Data Use Operational Framework’ [PDF] recognises that there is no single way of enabling or promoting data use, and that each operational setting requires a tailored approach. Our position evolved through data landscaping analyses of numerous national data ecosystems, which unearthed a range of insights on what good data use should look like.

There is growing consensus that the most sustainable solutions are built from the bottom up, centred on perspectives from national and subnational data users. Time and again, we have found that when placing subnational data users at the heart of data ecosystems, data use is key, not only at the point of service delivery, but also during collection. This drives up data quality and provides the essential elements of a sustainable foundational system. However, far too often, international investments in national data systems tend to target international data users. This leads to duplication, competing priorities, and data that is collected many times and used once, rather than collected once and used many times.

As argued in our latest discussion paper ‘Data disharmony: How can donors better act on their commitments?’ , one of the greatest opportunities to resolve data coordination challenges lies in improved and transparent data governance, with countries creating a transparent mapping of their available data against their statistical needs in a national indicator framework. However, national data users often lack a central repository or even centrally held information about the data that is available. They also often highlight a lack of effective, secure and efficient data sharing.

Avoiding data graveyards

Put simply, if we don’t know what data we have and aren’t able to share it, we run the risk of creating ‘data graveyards.’ For those unfamiliar with the term, this occurs when data sits unused, eventually becoming lost and forgotten, despite having a potentially endless lifespan. Billions of gigabytes of potentially useful data are generated every day, but much of it meets this fate.

In February, I discussed this issue with colleagues from Open Data Watch (ODW), the Thematic Research Network on Data and Statistics (SDSN TReNDS) and the Statistical Institute of Jamaica at a UN Statistical Commission side event . While we still have much to learn, the event underscored the great strides the data community is making to transform national statistical systems for maximum data uptake, use, longevity and impact. All attendees highlighted the need for a sharper focus on dissemination that moves beyond publication towards uptake and use. The Statistical Institute of Jamaica presented on how it is supporting this aim by publishing data in open formats and increasing the use of infographics and social media, founded on a strong cooperation with national and subnational data users and an understanding of their needs.

ODW and SDSN TReNDs, supported by GIZ, presented a framework aimed at avoiding data graveyards that matches data-use barriers with solutions that data producers within national statistical systems can apply. As the project team continues to refine and develop the framework, I would urge anyone working on this issue to provide feedback by emailing Lorenz Noe, Research Manager.

Data kitchens: a recipe for success?

The discussion got me thinking – if we are avoiding data graveyards, what are we trying to create? We often hear terms like ‘data lake’ and ‘data warehouse’, but for me these analogies don’t quite capture the new and creative statistical systems we need. I think what we should aim for is something more like a kitchen: a space where we can use basic foundational ingredients (surveys, censuses and administrative data), combine them with innovative flavours (big data, geospatial data and community- and citizen-generated data) and bake them into public goods using our ever-evolving data engineering and analysis expertise.

Above all, we must ensure that we are always meeting the needs of national and subnational data users who are key to sustainable foundational systems. Whatever we create must satisfy the hungry, or our efforts will go to waste.