Reflections on year one of the Learning Zone: what we produced

By Zara Rahman

One year ago, we began work on the research and learning aspect of DataShift. We decided to call the space for this work the Learning Zone, and we used it as a way to learn more about how citizen-generated data is being used, worldwide.

Since then, we’ve carried out and commissioned a number of research and learning outputs through the Learning Zone. We were lucky enough to work with people pushing the boundaries of citizen-generated data in their respective fields, carry out research of our own, and partner with research teams in other countries to see what we could learn, together.

Below follows a short summary of all the work that was carried out under the Learning Zone, from August 2015 until June 2016.

Understanding the field

Recognising that there’s a lot going on under the broad label of ‘citizen-generated data’, we started off by trying to get a better understanding of what’s already out there. We commissioned Anca Matioc to write a series of 10 case studies looking at innovative or unusual citizen-generated data initiatives, which we published online iteratively. Putting energy towards profiling just some of the fantastic initiatives that we came across gave us, and the broader community, a better understanding of existing initiatives.

One thing we realised quickly though was that citizen-generated data exists under many different labels. With this in mind, we commissioned seven thought-leaders working with citizen-generated data in different sectors to write about how they use it and why, in a series of essays entitled Citizen-generated data in practice. These essays played three roles: joining the dots between people using citizen-generated data in different sectors, helping DataShift as a whole to widen its network and reach, and learning more about the approaches, challenges and lessons-learned from existing citizen-generated data initiatives.

Exploring deeper

Last August, we put out a call for researchers based in the DataShift pilot areas of Argentina, Kenya + Tanzania, and Nepal, to look into the impact of citizen-generated data initiatives in their respective areas. We recognised that there were time and resource constraints in what we were asking people to do – so we asked the researchers themselves to determine what ‘impact’ was in that context.

We worked with three teams in the three pilot locations, and in April 2016, published a series of three reports from each of them, all available to read online. 

Last October, a couple of events that we attended inspired some further writing and exploration:

  1. Firstly, following the Media Party in Buenos Aires, we attended a roundtable meeting with Argentine civil society organisations and government representatives, hosted by the City of Buenos Aires Innovation and Open Government Lab (Laboratorio de innovación y Gobierno Abierto de la Ciudad de Buenos Aires).
  2. Then, I had the chance to attend the Eye on Earth summit, where I learned a lot about the realities of collaboration between institutions and civil society on a practical level under the banner of ‘citizen-science’, an alternative label to citizen-generated data in this field.

All of this brought up the idea of using citizen-generated data not just as a way of understanding the world better, but as a tool for collaboration between institutions and civil society. So, together with Christopher Wilson, we co-authored a short piece called Citizen-Generated Data and Governments: towards a collaborative model, where we explored existing models of data collaboration, and outlined our first thoughts on the benefits and obstacles this kind of model might face.

But with this kind of frame in mind for future possibilities, we were wary of skipping ahead, or not taking into account what’s currently going on when it comes to data collaboration between civil society and governments. So, we commissioned Open Knowledge to look at how citizen-generated data is currently influencing the way in which governments and institutions carry out data collection. This piece, Changing What Counts, was published in March 2016. It describes a number of ways in which citizen-generated data has affected government data collection in the past and present, together with recommendations for making the process easier in the future.

Getting meta: presenting our learnings

We wanted to use the Learning Zone as a way to reach new audiences, as well as those who might be more drawn to more traditional, PDF-style reports. So, we published a few of our research findings directly online through specially designed sections of the DataShift site, as well as trying wherever possible to break up information into chunks so that it is easy to navigate.

The Changing What Counts report, for example, is available directly online on the site, as well as in PDF, as are the essays on Citizen Generated data in practice. Doing this also made the content of the research more accessible to readers: allowing visitors to link to specific sections of these resources. We also blogged on the DataShift site about all of the research we were doing, as we went.

As with all of the content on the DataShift site, we also released all of our research findings under a Creative Commons ShareAlike License. We encourage others to take what we found, and remix or re-use it in their work. We would be delighted to see the work we’ve done spread further.

Conclusion

As this phase of the Learning Zone wraps up, we’re proud to have worked on such a variety of topics and issues under the broad umbrella of citizen-generated data. We’ve managed to learn a lot about the way in which citizen-generated data is currently being used, and explore new possibilities for its use and broader impact in the future. We hope others can also learn from what we’ve found.

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