What data do we need? The story of the Cadasta GODI fellowship

This blogpost was written by Lindsay Ferris and Mor Rubinstein

There is a lot of data out there, but which data users needs to solve their issues? How can we, as an external body, know which data is vital so we can measure it? Moreover, what to do when data is published in so many levels – local, regional and federal that is so hard to find?

Every year we are thinking about these questions in order to improve the Global Open Data Index (GODI), and make it more relevant to civil society. Having the relevant data characteristics is crucial for data use since without specific data it is hard to analysed and learn.

After the publication of the GODI 2015, Cadasta Foundation approached us to discuss the results of GODI in the land ownership category. Throughout this initial, lively discussion, we noticed that a systematic understanding of land data in general, and land ownership data in particular, was missing. An idea emerged: What if we will We decided to bridge these gaps to build a systematic understanding of land ownership data for the 2016 GODI.

And so came to life the idea of the GODI fellowship. It was simple – Cadasta will have a fellow for a period of 6 months to explore the publication of data that is relevant to land ownership issues. The fellowship would be funded by Cadasta and the fellow would be an integral part of the team. OKI would give in-kind support of guidance and research. The fellowship goals were:

Global policy analysis of open data in the field of land and resource rights
Better definition for the land ownership dataset in the Global Open Data Index for 2016;
Mapping stakeholders and partners for the Global Open Data Index (for submissions);
Recommendations for a thematic Index;
A working paper or a series of blog posts about open data in land and resource ownership.

Throughout the fellowship, Lindsay conducted interviews with land experts, NGOs and government officials as well as on-going desk research on the land data publication practices across different contexts. She established 4 key outputs:

Outlining the challenges of opening land ownership data. Blog post here.
Mapping the different types of land data and their availability. Overview here.
Assessing the privacy and security risks of opening certain types of land data. See our work here: cadasta.org/open-data/assessing-the-risks-of-opening-property-rights-data/

4.Identifying user needs and creating user personas for open land data. User personas here.

Throughout the GODI process, our aim is to advocate for datasets that different stakeholders actually need and that make sense within the context in which they are published. For example, one of the main challenges in land ownership is that data is not always recorded or gathered by the federal level, and is collect in cities and regions. One of the primary users of land ownership data are other government agencies. Having a grasp of this type of knowledge helped us better define the land ownership dataset for the GODI. Ultimately, we developed a thoughtful definition based on these reflections and recommendations.

For us at OKI, having someone dedicated in an organisation that is an expert in a data category was immensely helpful. It makes the index categories more relevant for real life use and help us to measure the categories better. It helps us to make sure our assumptions and foundation for the research are good. For Cadasta, having a person dedicate on open data helped to create a knowledge based and resources that help them look at the open data better. It was a win – win for both sides.

In fact, The work Lindsay was doing was very valuable for Cadasra that Lindsay time was extended at Cassata and she worked on writing a case study about open data and land in Sao Paulo and Land Debate final report and a paper on Open Data in Land Governance for the 2017 World Bank Land and Poverty Conference.

Going forward in the future of open data assessment, we believe that having this expert input in the design of the survey is crucial. Having only an open data lense can lead us to bias and wrong measurements. In our vision, we see the GODI tool as community owned assessment, that can help all fields to promote, find and use the data that is relevant for them. Interested of thinking the future of your field through open data? Write to us on the forum – https://discuss.okfn.org/c/open-data-index/global-open-data-index-2016