Reflections from Dr. Okan Turkes on development of shared rules – from metaphors to Common European Agricultural Data Spaces.
Context Sets the Pace, Meaning Holds Position
A Karate master and a Capoeira master step into the arena. The gong rings, and the exhibition kicks off. The Karate master strikes first. “You attacked me wrong”, the Capoeira master claims. The Capoeira master dodges next. “No, you defended incorrectly”, the Karate master replies. The Karate master steps in again. “That strike was valid”. The Capoeira master insists, “Then your interpretation is the problem”.
Before long, the exhibition shifts entirely from motion to confrontation, then fully into words, as each tries to convince the other of the righteousness of their practice.
This is a witty narrative I shared in the context of interoperability during a panel session at the CEADS General Assembly in Kaiserslautern. It is not an ode to combat in any form, nor is it intended to encourage or promote confrontation. It illustrates why the motive matters more than connection: shared experience depends on shared meaning and a common understanding of what is expressed, interpreted, and done together.
Real encounters may have no shared rules, which makes them unpredictable and risky. That is why martial arts professionals from different practices avoid them outside sport. With agreed rules, and ideally referees in place, they can engage safely in structured sparring.
This metaphor illustrates a communication dynamic that can also surface in almost any professional or business environment. Across commercial domains, operating models, and organizational contexts, and extending down into data models, system architectures, and low-level technical implementations, this is where interoperability most often breaks down in practice. Not in connectivity itself, but in interpretation after handshake.
Shared Motives in Agricultural Data Spaces
Interoperability value is not created by connectivity alone, but by aligning exchanges with clearly defined use cases that provide context for interpretation and use. In this sense, interoperability is not an abstract technical objective, but a mechanism to ensure that data, its technical representation, and its intended purpose remain consistently aligned across participants and systems. A central principle emerging from this approach is that data sharing only becomes meaningful when it is anchored in shared intent: what is being exchanged, for which purpose, and under which agreed conditions of use. This shifts the focus from unrestricted data flow to governed collaboration models where it is structured around concrete operational scenarios and user value creation.
This becomes particularly evident as agriculture continues its digital transformation. Farmers increasingly operate within a fragmented ecosystem of machinery from multiple manufacturers, farm management systems from various vendors, agronomic advisory services, sustainability platforms, certification schemes, and financial and insurance services. While these systems are largely capable of establishing technical connections, the real challenge emerges during operation. For instance, a single concept such as a “field boundary” may represent an operational zone for a machine operator, a compliance perimeter for environmental reporting services, and a legal entitlement boundary for subsidy administrations. In a similar way, sustainability indicators, operational events, and agronomic measurements can produce different outcomes depending on the underlying assumptions, calculation methods, and intended use defined by each providing or consuming organization.
CEADS is built on the principle that interoperability only becomes meaningful when collaboration is guided by a shared intent that defines why data is exchanged in the first place. Rather than introducing another agricultural platform or central data repository, it enables a federated ecosystem in which existing data-sharing initiatives, platforms, public authorities, machinery ecosystems, research infrastructures, and sectoral data spaces can interoperate while maintaining sovereignty over their own data. The objective is not consolidation, but coordinated value creation across distributed systems operating under shared principles.
Within this intent-driven framework, use cases act as the operational expression of shared purpose. They translate collaboration intent into concrete exchange scenarios by defining what is exchanged, by whom, under which conditions, and for which agricultural outcome. This ensures that interoperability is not reduced to enabling technical connections between platforms, but is anchored in a common understanding of purpose, so that each exchange contributes to a clearly intended operational or economic outcome.
From Interoperability to Agricultural Value Realization
For farmers, this shift is fundamentally outcome oriented. Interoperability is not an end, but a means to improve operational efficiency, reduce administrative burden, and enable new economic opportunities. In practice, this translates into fewer repeated data entries across platforms, less manual recalculation of sustainability indicators, and more reliable reuse of information as it moves between systems and organizations.
Delivering this requires interoperability that goes beyond connectivity. CEADS positions interoperability as a multi-layered capability spanning technical interoperability for system connection, semantic interoperability for shared meaning, organizational interoperability for aligned processes, and governance interoperability for consistent handling of rights, consent, and permissions. These dimensions are implemented through structured mechanisms such as use-case frameworks, identity and trust services, consent management, and governance models that move interoperability from principle to execution.
At the European level, CEADS contributes to broader data space vision by enabling use-case-driven interoperability across domains. This allows agricultural information to be exchanged with other sectoral ecosystems while preserving data sovereignty, trust, and consistent interpretation of meaning. The emphasis is not on centralization, but on enabling collaboration across distributed and existing initiatives.
Ultimately, CEADS success is measured not by data volume exchanged, but by the degree to which information can be reused with preserved meaning, trust, and control. This is what enables a federated, data-sovereign agricultural ecosystem on a European scale.
