Data Veracity Assurance in Data Spaces

Data Spaces are widely seen as a cornerstone of future data ecosystems, enabling sovereign, interoperable, and decentralized data sharing across organizational and sectoral boundaries. While much attention is paid to access control, interoperability, and governance, a critical question often remains implicit: How trustworthy are the shared data themselves?  This is precisely the gap addressed by Data Veracity Assurance.

What is Data Veracity Assurance?

Data Veracity refers to the credibility, reliability, accuracy, and overall quality of data. In open and decentralized Data Spaces, participants need more than contractual assurances or technical connectivity. They require transparent and verifiable information about data quality and trustworthiness—ideally in a machine-readable and interoperable form that can be evaluated automatically. While data providers need to ensure the data they supply is going to be used as contractually agreed, data consumers also have expectations about the data from a quality perspective—namely, that it will be fit for purpose and deliver genuine value for their intended use case.

Key ideas from “Data Veracity Assurance in Data Spaces”

The paper “Data Veracity Assurance in Data Spaces” by Bertalan Zoltán Péter, Nada Akel, László Gönczy, and Imre Kocsis provides a structured conceptual framework for embedding data veracity into Data Space architectures.

The authors present a conceptual model of data veracity assurance in the Data Space context and propose:

• two distinct forms of veracity assurance: Attestations of Veracity (trust-based declarations about data quality) and Proofs of Veracity (technically verifiable evidence),
• the combination of technical mechanisms (e.g., cryptographic proofs or validation services) with contractual and governance instruments,
• and the use of verifiable credentials to express data veracity claims in a standardized, interoperable, and decentralized way.

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Together, these elements form a coherent approach to making data trust explicit, assessable, and enforceable within Data Spaces.

From academic concept to Data Space infrastructure

These concepts are not purely theoretical. Within Prometheus-X, Data Veracity Assurance is defined as a dedicated Building Block of the overall Data Space infrastructure. Its purpose is to operationalize exactly the kind of mechanisms described in the paper.

The Prometheus-X Building Block translates the academic framework into practical architecture components by:

• enabling machine-readable veracity statements attached to datasets,
• linking veracity information to policies, contracts, and governance rules,
• and integrating veracity mechanisms into existing Data Space protocols and interoperability stacks.

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In this sense, Prometheus-X provides a concrete implementation context in which the paper’s ideas can be tested, refined, and deployed in real-world Data Space scenarios.

Conclusion

The paper “Data Veracity Assurance in Data Spaces” delivers an important conceptual foundation for one of the most critical challenges in Data Spaces: establishing trust in data beyond access rights and legal agreements. Prometheus-X builds directly on these ideas, turning them into actionable building blocks for interoperable and trustworthy data ecosystems. Together, they demonstrate that Data Veracity is not an optional add-on, but a core capability for sustainable and scalable Data Spaces.

Read the full paper here: DOI: 10.1007/978-3-032-05877-5_22