Coordinators: Christopher Wilson, The Engine Room and Jun Matsushita, information innovation lab (iilab)

The recent proliferation of open data sets for public good has not been matched by sufficient efforts to facilitate interoperability between relevant data. Whether due to political incentives of data producers and managers, or purely technical obstacles, the inability to quickly merge and mesh data sets surrounding specific issues is a point of frustration for many advocates and researchers. This session is dedicated to testing different approaches for merging and meshing data sets in different issue areas, or “data clusters”, to see what kinds of outputs can be quickly achieved and new projects initiated, specific to different types of data or data users, and how useful or lacking existing standards for interoperability might be in different issue areas.

Pressing issues, resources and opportunities for merging national and international data sets will be identified collaboratively, and then applied to 3-5 use cases, to produce advocacy materials, draft interoperability standards or plans for further action. The session will provide 4-5 prepared “data clusters” for use cases, with data sets on national issues such as resource extraction, aid data or internet access and routing, as well as a data cluster on international transparency and accountability initiatives. Use cases may also focus on national or international issues and data sets surfaced during the session.

The first half of the session will be devoted to identifying issues and approaches. The second half will be a collaborative hacking session on different use cases in small groups.

This session is not just for technologists, it will be driven by people of all different skill sets, who want to see the complementary use of data sets to impact or better understand specific issues. Each small group will have a co-facilitator with the hard skill necessary to tackle thorny issues of interoperability.

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