For data commons to become a (partial) solution to the issues caused by data monopolies, they need to be politicised. It is important to ask whose data is made common and, subsequently, whose city we will end up living in, write Gijs van Maanen and Anna Artyushina in the first of their two-part blog.
In 2020, the notion of data commons became a staple of the new European Data Governance Strategy, which envisions data cooperatives as key players of the European Union’s (EU) emerging digital market. In this new legal landscape, public institutions, businesses, and citizens are expected to share their data with the licensed data-governance entities that will oversee its responsible reuse. In 2022, the Open Future Foundation released several white papers where the NGO (non-govovernmental organisation) detailed a vision for the publicly governed and funded EU level data commons. Some academic researchers see data commons as a way to break the data silos maintained and exploited by Big Tech and, potentially, dismantle surveillance capitalism.
In this blog post, we discuss data commons as a concept and practice. Our argument here is that, for data commons to become a (partial) solution to the issues caused by data monopolies, they need to be politicised. As smart city scholar Shannon Mattern pointedly argues, the city is not a computer. This means that digitization and datafication of our cities involves making choices about what is worth digitising and whose interests are prioritised. These choices and their implications must be foregrounded when we discuss data commons or any emerging forms of data governance. It is important to ask whose data is made common and, subsequently, whose city we will end up living in.
What is data commons?
When the policy practitioners and researchers discuss data commons, they often speak about different things; while some define data commons as any form of collective governance over data, others argue for inherently anti-commercial and anti-capitalist conceptions of the term. The notion of data commons does not have a uniform definition. This terminological confusion may lead to the lack of trust in data commons on the part of data donors or to data being used in problematic ways. This discussion is especially relevant in the context of city governance as European municipalities actively engage in data sharing agreements and partnerships, seeking to reuse data for socially beneficial purposes.
The European Union’s 100 Climate Neutral and Smart City initiative will entail multiple data collaborations between public and private actors working together to create new, low-carbon urban infrastructure. Also, cities themselves actively re-imagine data commons through the concepts of public digital infrastructure and digital rights.
When it comes to smart cities, data commons can be defined as a way to collectively govern and manage informational resources and digitised urban infrastructure. There is a community in Amsterdam where neighbours collectively manage their energy-efficient heating system via analysing the data it produces, and a data-sharing hub created by Uber drivers who want to understand how their salaries and fines are being calculated—these are both examples of data commons. In both cases, a group of people pools their data together and uses this data for collective purposes.
There are other visions of data commons. The Open Future Foundation combines recent debates on business-to-government data sharing (B2G) with that of the data commons, to propose the establishment of a European-Union level data steward that acts as a “recipient and clearinghouse” for data made available by commercial actors. From various disciplinary backgrounds, academics, too, have argued for the relevance of data commons for countering and mitigating the problematic effects of capitalism. While some situate themselves in the free and open software movement, invoke the notion within the context of ‘AI capitalism’, or emphasise the useful socialist/Marxist heritage of the term, others presented more critical commentaries about the apparent incapacity of commons-like initiatives to structural change society, or questioned their techno-juridical characteristics.
The discourse of the data commons, in other words, is in flux and shows a huge diversity of social-political and economic presuppositions that guide and motivate different contributions. This makes it imperative to reflect critically on what kind of data commons one’s arguing for, for which reasons, and how invoking the concept solves what kind of problem. Using the concept ambiguously might result in problematic forms of ‘commons washing’.
Whose funding?
In practical terms, data commons are often understood as a form of data sharing between any types of actors including individuals, civic actors, research organisations, businesses, and governments. The majority of existing projects are at a pilot stage or have been framed as experimental initiatives. Scholars point to several trends when it comes to the city administrations’ data reuse initiatives: private actors don’t have much motivation to share their data unless there exist a clear economic interest; municipalities have enormous interest in accessing the data from commercial companies and other public actors, yet they rarely have financial means to support them; many of these initiatives are framed in normative terms as a response to the “hegemonic data governance models”. Indeed, while the municipalities and citizens tend to frame data as a public good or collective resource, commercial companies see data as a private asset.
Data commons initiatives are rare and often short lived. The lack of funding to cover the preparation of useful data sets and data storage are serious barriers to these projects. Among the initiatives that have survived beyond the experimental phase was the Silicon Valley Regional Data Trust, which pooled the resources from several US school boards, social services, and research organisations to examine the needs of schoolchildren in California. The trust was a conventional example of data commons as only the organisations that have contributed data had access to it, and the decisions were made collectively. This project relied on the grant from the National Science Foundation (NSF) and the resources of the University of California to support its work. After the grant expired, the initiative was put on hold. As such, it is in line with the trend found in the scholarly literature: to survive and be useful, data commons require public funding. In the UK, the App Drivers & Couriers Union (ADCU) had created a data trust for the drivers, where they could get data analytics insights that helped them bargain with the employers. The fate of the data trust, however, is unclear as Uber and Ola jointly took the drivers to court for the “data tampering.” An example of a functioning, privately-run data commons with a clear collective purpose is a knowledge trust established by the fisheries businesses. The trust pools together data from various companies to create the maps of marine resources, flag environmental issues, and establish collective sustainable energy solutions. To sum up, data commons are believed to have an immense potential in leveraging data for socially beneficial purposes.
Read part two of Whose data commons? Whose city?
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The views and opinions expressed in this post are those of the author(s) and not necessarily those of the Bennett Institute for Public Policy.
