Mobility data as a commons – towards a common mobility data infrastructure
"Today, the most important digital innovations, especially in the field of artificial intelligence, can only develop their full potential when large amounts of data are made available and processed to derive knowledge from it" argues Lucie Kirstein, Senior Manager Strategic Projects at acatech – National Academy of Science and Engineering, and coordinator of the EU-funded preparatory action to establish a common European data space for mobility, in her recent opinion piece reflecting on the discussions of the 10th Florence Intermodal Forum.
This article by Lucie Kirstein, Senior Manager Strategic Projects at acatech – National Academy of Science and Engineering, and coordinator of the EU-funded preparatory action to establish a common European data space for mobility, originally appeared in the European Transport Regulation Observer “Creating a common European mobility data space” (February, 2023).
There are several domains in which Europe is falling behind other large economies. One is the ability to harness the potential of data. Giant tech firms in the U.S. increasingly act as knowledge and information gatekeepers engaged in extensive technology enclosure – made possible thanks to the harvesting and processing of large amounts of data stored on their customers’ clouds. This has led to the emergence of unprecedented power asymmetries with severe effects on European businesses and individuals, the “rule by data”, as Katharina Pistor frames it.
Today, the most important digital innovations, especially in the field of artificial intelligence, can only develop their full potential when large amounts of data are made available and processed to derive knowledge from it. In the mobility domain, strengthening public and shared transportation as a backbone for sustainable mobility in Europe depends on the availability and linkage of large datasets. For example, mobility data can provide valuable insights regarding movement patterns that can help address questions in the public interest, including sustainable urban planning and the provision of public services. In rail, the availability of large amounts of data is the basis for more capacity, punctuality, and efficiency in railway traffic, and hence massive savings and increased attractiveness.
Limited data availability for innovation
Despite efforts, many mobility-related data remain confined in silos, unused by big tech and not shared among peers or made open to the public. The lack of widespread data sharing in Europe can be seen as a market failure, as it fails to reach its full potential for the benefit of society. In the sense of the famous game-theoretical prisoner’s dilemma, there are economic disincentives for actors to share data with each other. If only one actor shares data, all others benefit. In forming their expectations, all actors anticipate that other actors will shy away from sharing their data. This leads to low data availability overall. If actors nevertheless decide to share data, there is a danger of free riding: the benefits from improved data availability accrue to actors who do not have to provide anything in return. The concept of data altruism, as used in the Data Governance Act, illustrates this notion of data sharing without return.
However, it is unlikely that data altruism will become widespread and a mandate for open data in all sectors is met with scepticism. To reap benefits from data sharing while bypassing emerging power asymmetries, a possible solution is the sovereign, decentralised sharing of data organised by a central trustee. At acatech, we believe that improving data availability for the benefit of society can be achieved by creating a shared data infrastructure and services that provide fair regulations, contractual agreements, and incentives. In other words, the evident market failure points to the necessity of a public European project, treating mobility data as a public good or as part of the commons.
As opposed to monopolising informational content and governance power, the idea is to build a democratic and transparent organisational structure that allows increased collective benefit from mobility data. Information asymmetries will be limited by improved discoverability of data (e.g., through an open central catalogue) and transparency of logged transactions. Free data production and loss of control can be mitigated by digital tools to enforce usage policies and monetise data to allow for fair shares in value-creation. Transaction and search costs (“economies of speed”) can be lowered by creating a one-stop-shop for mobility data in Europe. Interoperability avoids fragmentation of the data economy and lowers integration costs. Finally, such ecosystems allow multi-sided transactions and business models without typical power concentration seen in big multi-sided platforms.
How could a common European data space for mobility look like?
A practical application of principles such as fairness, trust and data sovereignty can be realised in a common European data space for mobility. There is a myriad of options when it comes to building the business, legal, operational, functional, and technical dimensions of a data space.
Data spaces can be set up in a centralised or decentralised manner. This means that a neutral trustee provides central services to all data space participants or that an orchestrator manages a set of federated services provided by different parties in the ecosystem. In terms of organisational models, two main approaches are emerging: (a) a mobility data space as a voluntary, private marketplace proposing added-value services facilitating discoverability and lowering participants’ transaction costs in accessing data, and (b) a public digital infrastructure (managed e.g. by a public utility company) erected on top of the physical infrastructure to facilitate data flows via harmonised, open components, built around National Access Points and shaped by strong policies and regulations.
Both approaches can be conciliated by making sure adequate funding is available for an agency or neutral organisation to manage and operate the common technical infrastructure and allowing the on-boarding of numerous public and private stakeholders to achieve the desired network effects. Ultimately, to limit monopolistic behaviour and sector fragmentation, massive investments are needed to achieve a decentralised, sustainable, and commons-based data economy.
 Hinting to the enclosure movement, the term refers to the extraction of value from data as “commons” (intangible or informational resources under collective ownership or without prior coded value or property). The last decade gave rise to a commodification of data in ways similar to what Polanyi described as fictitious commodities. See e.g., Vatanparast (2021), “The Code of Data Capital: A Distributional Analysis of Law in the Global Data Economy”, Juridikum 1/2021, 98-110, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3832471.
 Rikap (2022), “Big Tech: Not Only Market But Also Knowledge and Information Gatekeepers”, https://www.ineteconomics.org/perspectives/blog/big-tech-not-only-market-but-also-knowledge-and-information-gatekeepers.
 Pistor (2020), “Rule by Data – The end of markets?”, 83(2) Law & Contemp. Probs. 101, https://scholarship.law.columbia.edu/faculty_scholarship/2852.
 Overdiek & Schwab (2023), “Ein Datenclub als Booster für die digitale Transformation”, https://makronom.de/ein-datenclub-als-booster-fuer-die-digitale-transformation-43354.
 Data altruism refers to individuals and companies giving their consent or permission to make available data that they generate – voluntarily and without reward – to be used in the public interest.
 See e.g., OECD (2018), “Rethinking Antitrust Tools for Multi-Sided Platforms”,
 See e.g. the Flemish Data Utility Company, https://www.vlaanderen.be/digitaal-vlaanderen/het-vlaams-datanutsbedrijf/the-flemish-data-utility-company.
 Network effects imply that once digital platforms have reached a certain size, they are likely to tip. This comes close to the idea of natural monopolies where technological developments result in various forms of economies of scale related to the access to data, the use of algorithms and prediction. See e.g., Ducci (2020), “Natural Monopolies in Digital Platform Markets”, Cambridge University Press, https://www.cambridge.org/core/books/natural-monopolies-in-digital-platform-markets/1EA207B0EB21EAFDC0197DA511C5E0BA.