Appendix: Two case studies

This appendix has two purposes.

The first is to apply the theory of the Data Commons to some real-world cases and illustrate what those high-level community principles might look like when put into practice. If we could form a Biosphere Data Commons or a Person Data Commons, what will that enable?

The second (meta) purpose is to rehearse the kinds of question that any such Community of Interest would need to answer before they could begin building their own Data Commons.

Two case studies informed this investigation of designing and building a Data Commons. Using these real-world challenges provided a useful foil to test thinking and develop the ideas in this report. These two data integration and reuse case studies illustrate some of the concepts, community questions, and value propositions of a Data Commons approach.

The first case is the example of New Zealand biosphere data integration and reuse.

This is an example of the kind of commons where there are highly aligned interests in integrating and reusing data, and where their data can be relatively open access: there are fewer personal risks or commercial sensitivities. It also illustrates integrating data by place. There are several shared goals around which the community can align to scale up data reuse, such as the massive national undertaking to make NZ predator-free by 2050, the need to manage our nation’s unique indigenous bioheritage, and the need to stop new invasive pests entering New Zealand.

The second case study is about the integration and reuse of personal data.

It is at the other end of the spectrum, where licensing semi-open access to highly personal data becomes a key consideration. How do we design a Data Commons that allows us to license some kinds of open use of personal data whilst limiting other kinds of use to consent only? The same kinds of consideration might also apply as lessons for the management of commercial sensitivities around data integration and sharing. This case study illustrates integrating data by person. One burning issue currently in New Zealand is the state sector’s poorly realized desire to integrate and reuse government data to support social investment. On a more positive note, there are emerging opportunities for personalised health, big-data-based science, and accelerating innovation if only New Zealand could unlock the potential for low-friction access to integrated personal data by keeping it high-trust and safe for people.

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