Going in, I had many questions about federation. The Data Spaces Support Centre has a relatively expansive definition of federation, speaking in broad terms about aligned rules on governance, including shared trust frameworks and shared business interests. But this level of alignment seems unrealistic to me, or at least it’s unrealistic without a central driver of some kind to bring parties together.

And this was the goal of the role play that we would run—to understand whether and how federation would form when a fictional real-estate developer of a smart community would require access to data across multiple data spaces. Here’s a bit more information on how we set up the role play, but feel free to skip over the summary.

An in-built premise: a Member State would drive federation

An important component of the role play is that each actor in the play receives a briefing that outlines not just the scenario, but also their motivations. We, as the builders of the role play, try to accurately reflect the intrinsic motivations of each stakeholder, but we also provide individuals with enough incentives to move the scenario forward and potential conflict points to reveal frictions.

In this role play, we had actors from both the private and public sector, including two national governments, two privately oriented data spaces, one city (with both data and the land for the smart community), and one private-sector consultancy with expertise in data spaces. We expected that the mix of public and private goals and incentives for participating would reveal some of those important frictions. This is a tension that we see every day in projects funded by Horizon Europe. As such, it was pretty easy to write a briefing to bring these elements out.

What was not immediately clear was how to drive the discussion of federation forward. The use case around which we build the scenario provided the impetus to bring together disparate data sets that might benefit from a federation that eases burdens accessing data. But just because there is a reason for people to come together does not mean that going through the inevitable negotiations around federation would make sense. After all, the status quo of negotiating with individual data holders–a process that would still be necessary even when dealing with data spaces–is a viable option with less initial overhead.

After much thought and debate, our belief was that an individual Member State was the most likely to start a conversation around federation, at least within our scenario. And so, as a part of the briefings, we gave a Member State clear incentives to drive federation and to be seen as a leader. It was made clear that money was available. The smart community was described as a test case and part of a broader digitalisation drive for economic competitiveness, meaning there was also political capital to spend. It was hard to put more motivation in their to lead the case for federation, and the actor playing that role certainly tried their best to make the case.

But, the Member State never did get any traction for federation.

The private sector took the lead (eventually)

It was, in fact, the consultancy and the two private-sector data spaces that presented the more credible case for co-operation and started to talk in terms of signing deals–though this only took place after some hours of discussion and debate. Despite the clear incentives and motivations of the leading Member State, private actors wanted to see the national government only play a steering role, distributing resources rather than being an orchestrator or leader of the community.

Even the local government from the Member State did not become a natural ally for a public-sector driven solution. They did not pick up and support the national governments desire to lead, rather viewing them as one stakeholder of many, focusing on their own needs rather than national ones. This makes sense, too. At the end of the day, the public sector is not a monolithic entity, and there are always frictions between different governments, whether that be disagreements between national governments or disagreements between national and regional ones. And the local government was looking for the most viable solution that would protect its interests.

Why did the private sector lead?

Despite the briefings explicitly mentioning public-private partnership—and even an intervention where we made it all the more explicit that all actors had ‘honest intentions’ in the negotiation—there was an ongoing disconnect between the actors that were public and privately oriented. Public actors simply had larger and more complex motivations to participate, looking to not just offer data and services that the developer would need, but also wanting to ensure that a broader public good was met.

These wider interests led to discussions that were, for the real-estate developer, outside of the scope of their interest and sometimes even felt like they could be a distraction. Importantly, it also increased the number of problems that would need to be resolved before any work could begin. The narrower focus for the private-sector parties helped them to stay on a more focused path, which allowed them to progress more quickly and not get pulled into wider discussions about digital sovereignty, data rights, and other (legitimate) public interests.

An added wrinkle: the weak value proposition for federation (and data spaces in general?)

While six hours of role play did see some convergence, the players ultimately came to option 2, forgoing federation. One point that was made clear was that the value proposition for the federation (or even the data spaces) was weaker than expected—and this came down to a key legal point. While joining a data space created obligations for onboarding, it did not resolve a significant obstacle, namely the need to make agreements with each of the data holders within those data spaces. Some participants assumed that the negotiation was unnecessary, and that signing up for the data space meant that all data would become available. In some cases, it was suggested that the governance authorities of the data spaces could help facilitate those discussions, but given the nature of the data (which in many cases would be personal), any kind of generic agreement would not suffice.

Incomplete lessons: an n of 1 and letting it play longer

Of course, this is only a single exercise, and the role play could have played out for longer to understand better whether the Member State would accept a secondary role, helping to lay conditions to facilitate distrust between private actors that would undoubtedly come to the foreground the longer that a negotiation would take place. And of course, lessons here need to be put into a broader context of data spaces (and federations) of differing scopes and purposes. I would expect, for example, that if we ran a role play on digital product passports, where compliance to public sector requirements is a driving goal, that it would have led to a completely different dynamic. Nonetheless, in a context where private interests are a driving factor, the private sector seemed best placed to move things forward.

Next step: supplementing lessons with Agentic AI?

While it would have been great to have our actors for another day or two to continue the negotiation and see how the scenario would continue, people’s schedules (and perhaps energy levels) simply wouldn’t allow for it. It would also be helpful to run the scenario with different people to see if the same results would come about. While this does not seem to be a realistic option in a face-to-face setting, it doesn’t preclude using agentic AI–using our briefings for the appropriate prompts–to re-run the role play, tweaking the scenario and briefings to what changes it would bring about.

I’m currently using crewAI and have run the scenario once or twice using gpt-4o-mini to see what the result would be. I would hope my next post will address some of the results.

Now, does someone want to give me some tokens to play with?

This set me thinking about the legal agreements that should form the basis for the data exchanges taking place within a data space. The fact that legal agreements should exist to share data is not new or unique to data spaces. What would make this unique is if a data space has a specific legal form and framework for this rule creation.

To explore what this means, I find it instructive to explore existing organizational forms and the (legal) structures and obligations that they create for organizations.

A limited liability company, for example, follows particular norms when it comes to rule setting and organizational structure. While these rules can differ by Member State, they are set out by law and give a limited liability company a clearly identifiable form.

The organisational clarity of a limited liability company

A limited liability company requires articles of association or similar founding documents that must be registered with the appropriate authorities. These articles outline governance rules, capital contributions, profit distribution, and transfer restrictions. Many jurisdictions require a minimum share capital.

Some basic elements about how these types of companies are governed are also mandated. A limited liability company typically must hold at least one general meeting every year to approve accounts and address member resolutions. Important decisions are documented in minutes, which are also publicly available.

On reporting, most European limited liability companies must also file annual accounts with a commercial register, making basic financial information publicly available. Depending on company size, these may need to be audited. Many jurisdictions also require a register of members and, increasingly, a register of beneficial owners for anti-money laundering purposes.

Limited liability companies still have a lot of leeway in how they choose to operate and manage themselves. Nonetheless, there are commonalities between all limited liability companies that are embedded in the law.

Data spaces, as defined by the Data Spaces Support Centre, lack this organisational clarity

Returning to the data space, it lacks any kind of law or convention around how it needs to govern itself to be defined as a data space. If I read the building block labelled as organizational form and governance authority from the Data Spaces Support Centre (DSSC), I see decision trees that give many options: in fact, one of the forms for the governance authority that should represent the data space is a limited liability company. But the data space and its governance authority can assume other legal forms as well, including:

• A European Digital Infrastructure Consortium (EDIC), a special legal form which resembles European Research Infrastructure Consortium (ERIC), which support cross-border organisations that are largely publicly funded.
• A European Cooperative Society, which is a non-profit with characteristics of a cooperative and public limited company.
• A European Economic Interest Grouping, which is a non-profit legal entity similar to general partnerships, where members share unlimited liabilities, which flow through to the founding entities.

Each of these forms has specific rules around how they are organized, including how rules are formed and key decisions are made.

At the same time, the building block informs me that a data space can also be unincorporated, without legal form, where rules around rule-making are going to be decided according to an agreement between the various parties that are running the data space. Yet another organisational form that a data space can assume.

The DSSC ‘design principles’ do not help formalise how a data space is governed

Yes, the DSSC also provides a set of high-level ‘design principles‘, describing aspirations (not obligations) on transparency and inclusivity, among other principles. There are brief mentions of rulebook designs by organisations like the International Data Space Association (IDSA) and Sitra, but these are not requirements.

More importantly, there are inherent tensions in some of the principles whose resolution will be determined according to the legal shape of the data space. For example, governance authorities in data spaces are often composed of voting members, which is likely a small subset of the participants in the data space. Because their interests may not reflect all participants equally, there is a structural tension between full transparency and representative decision-making.

Without explicit mechanisms for inclusive representation or conflict resolution, how this tension is resolved likely depends on the legal form of the governance authority. If that’s a limited-liability company, the stated principle of full transparency will likely suffer.

As data spaces evolve, I would expect a clearer organizational form to develop

This ‘long walk’ leads me back to my original definition of the data space, which is the fact that a governance authority sets the rules for the data space in some form; however, this rule-setting function isn’t (yet) defined by law or convention, excepting the rules around the legal form that the governance authority may end up assuming. The fact that a data space has a governance authority remains a defining characteristic, but how those rules are established and enforced is very much an individual decision at the moment.

Tja. Terug naar governance.

Het eerste wat ons opvalt, is dat mensen het verschil tussen data governance en organisatorische governance niet scheiden. In de eerste instantie praten wij over permissies en identificatiebeheer wanneer mensen data willen delen. Mag u mijn data gebruiken? Dit is de essentiële vraag. Met organisatorische governance praten wij over de regels van organisaties die moeten samenwerken. Ja, er is overlap. Organisaties maken de regels voor data governance. Maar het zijn nog steeds verschillende overwegingen.

Het tweede wat ons opvalt, is dat mensen over governance willen praten als een op zichzelf staand onderwerp, maar governance vloeit voort uit specifieke doelstellingen. En het woord ‘specifiek’ is belangrijk. De doelstellingen zijn meer dan ‘ethische beslissingen’ maar combineren politieke, economische en sociale doelstellingen. Verduidelijk eerst die specifieke doelstellingen en praat dan over governance.

Misschien kan de Nederlandse taal ons redden. Kunnen wij niet over regeringsvorm en gegevensbeheer praten? Wat zijn de beste Nederlandse woorden te gebruiken?