In five posts, I want to speculate about the next twenty years of open data based on the past twenty years of open source. The idea is to transfer what we learned from open source in one way or another to open data.
This is part 4 on creating and leading open data projects.
Open data foundations
Like in open source, I expect companies to band together to create open data projects that counter a data monopolist. The necessarily resulting open data foundation creates an equal and fair playing field for all participants and provides the backbone that supports the open data project.
The involvement of commercial entities with current volunteer projects, like OpenStreetMap, may well create a strain on the community. Clear governance is necessary to sustain such involvement. In general, commercial involvement under clear rules is beneficial, as it adds diversity and makes projects more sustainable.
Commercial open data
Like in open source, commercial open data companies will provide open data as a useful resource, to which they offer complementary data, services, assurances, computation, what-have-you. This provision of open data will probably not allow for open collaboration on the data, but rather be a business strategy for the vendor behind the commercial open data.
Like in open source, proprietary data providers may want to label their data as open without actually using an appropriate license. The goal is to ride on the goodwill of the term open without actually providing its benefits. Given the remaining broad lack of knowledge, this play may well be (somewhat) successful.
Beyond these three items, there are more commercial and not-so-commercial models of how and why people and companies alike may create open data projects. Maybe I’ll get to it in some future posts if there is any interest here in talking about open data.
Next up: Inner data.
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