“A data space is a virtual space leveraging existing standards and technologies, as well as governance models well-accepted in the data economy, to facilitate secure and standardised data exchange and data linkage in a trusted business ecosystem. It thereby provides a basis for creating smart-service scenarios and facilitating innovative cross-company business processes, while at the same time guaranteeing data sovereignty for data owners” [1].

Common European data spaces across strategic domains are at the heart of the Data Governance Act [2], a crucial component of the European strategy for data that entered into force in early 2024. Data spaces encompass both private and public players, and they extend to sectors such as energy, environment, mobility, manufacturing, agriculture, finance, public administration, etc. The schematic below displays the technical and governance building blocks of data spaces:

• Interoperability
• Trust
• Data value
• Governance

The three main prerequisites – according to the European strategy for data – that help to deliver the expected benefits of data spaces to end users are detailed below:

• A secure and privacy-preserving infrastructure to pool, access, share, process, and use data.
• A clear and practical structure for access to and use of data in a fair, transparent, proportionate, and non-discriminatory manner, involving clear and trustworthy data governance mechanisms.
• The fulfilment of European rules and values, in particular personal data protection, consumer protection legislation, and competition law.

A recent report by the Energy Transition Expertise Centre (EnTEC) [3] details a roadmap to build a Common European Energy Data Space, aimed at serving flexibility to related players and services on the European energy market or at high technological readiness levels in European research projects.

Challenges to reach the scope are:

• Standards compliance.
• Technical capacities of widespread adoption of applicable data standards.
• Effective use by an integrated energy market that observes system data commons.
• The complex legal framework for software licensing possibly leading to conflicts with the institutional policies of the contractors.
• Open-source software might be inadequately supported.

The main benefits of energy data spaces are:

1. Data reuse [4]: The “measure appropriately/use many times” principle is foreseen to increasingly underpin the optimisation of the entire framework for the pan-European transmission network development and its impact on power market design. An open data policy assumes that open, accessible data will spur innovation and further catalyse systemic efficiencies.
2. Data preservation [4]: Data spaces facilitate the long-term preservation of archived quality data (with associated metadata and provenance information):
   • Protecting significant public investments in costly network data collection.
   • Ensuring the preservation of reliable electricity system data that are unique in time and space.
   • Irreplaceable for diagnosis and understanding of rare but possibly highly impacting events (such as blackouts or poor customer response to market signals).
3. Data integration [4]: Many data management efforts within TSOs are organised around an observing platform, namely digital fault recording, power congestion, or meteorological recordings. In the early stages of data lifecycles, managing all data from a single platform in a single place appears more efficient. Nonetheless, players involved in mathematical modelling or operational decisions prefer using data organised around a sampling method (e.g., electricity consumption data for family homes) or based on essential atmospheric variables (e.g., local wind speed or sun irradiance). Creating such integrated data sets is easier if all source data sets are available within interoperable standards and compliant formats.
4. Reducing lifecycle costs of IT tools [4]: Data interoperability is instrumental when developing an operationally sustainable energy data space as it generates significant cost savings and scalability thanks to automated data fetching and access. Standards compliance minimises the likelihood that custom, unmaintainable, and invariably costly-to-implement one-off solutions for handling of data are implemented. Software development is also an essential yet costly part of data management lifecycles. Moreover, when developed using open-source software principles and methods, generic tools can attract more developers as they can be managed as a team working on a common tool rather than individually on their own application. This type of management increases software quality (documentation and software tests) and the developer community’s efficiency. Nonetheless, open-source software policies accompanying open data sharing policies have long-term impacts.

The data space technology supports achieving the target policies set by the Data Governance Act [2].

The construction and use of data spaces require that the stakeholders – i.e. data producers/providers and consumers – implement the following building blocks and adopt appropriate data access means [5]:

• Interoperability building blocks ensure that any data published can be technically consumed by any data consumer entitled to do so. Moreover, each data consumer can be certain that they can technically access and use any data made available by any data provider. The following building blocks belong to this category:

  • Data models and formats
  • Data exchange APIs
  • Provenance (also called “data lineage”) and traceability

• Trust building blocks ensure a high level of confidence between the communication partners due to the importance of data confidentiality. The following sub-blocks form this category:

  • Identity management
  • Access and usage control
  • Trusted exchange

• Data value building blocks cover essential aspects from the perspective of handling data as economic assets. This can be achieved using:

  • Metadata and discovery protocol
  • Data access/usage accounting
  • Publication and marketplace services

• Governance that regulates the business relationships between the different roles in a data-driven business ecosystem: data owner, data acquirer or data provider, data processor, data marketplace Operator.

Moreover, it is necessary to mention additional enablers, such as:

• Stakeholders – i.e. data producers/providers or consumers – are the key stakeholders who will enable energy data spaces accompanied by their responsibilities.
• Data access services realised by nodes of a distributed system of providers and customers requires APIs designed for web protocols.
• Metadata exchange and data discovery services supporting data discovery to ease developing and adhering to interoperability standards.

Several EU-funded, ongoing projects are addressing the deployment of energy Data Spaces, as detailed in the table below:

Table: EU-funded projects are addressing energy Data Spaces.

Candidate architectures for the IT solution that take the building block approach include the Gaia-x [12], Smart Grid (SGAM) [13], and BRIDGE architecture models [14]. The current R&D issues faced by energy data spaces for network operators are:

• Tackling interoperability issues early in the data lifecycle, as close as possible to the production time.
• Interoperability testing to verify that components within the application, server, and database work together. The expected results are expected by both data providers and data users. The CONNECTATHON concept used for a medical data space could be a starting point [15].
• Engaging and partnering further with in-situ sensors and IT platform manufacturers to ease the production of standards-compliant data outputs natively at source.
• Managing data quality (completeness, consistency).

The technology is in line with milestone “Interoperable data spaces for seamless and secure energy-related data transfer” under Mission 4 of the ENTSO-E RDI Roadmap 2024-2034.

Examples

TRL 8/9 for the ENTSO-E transparency platform with improvements following the external audit [10].

1. data.europa.eu, “data.europa.eu and the European Common Data Spaces”.

2. European Commission, “Common European Data Spaces”.

3. V. Berkhout et al., “Common European Energy Data Space,” ENTEC report, 2023.

4. D. Snowden et al., “Data Interoperability Between Elements of the Global Ocean Observing System,” Frontiers in Marine Science, vol. 6, p. 442, 2019.

5. International Data Spaces Association, “Our mission, Creating the future of the global, digital economy”.

6. Omega-X, “Concept”.

7. EDDIE, “About EDDIE”.

8. Enershare, “The Energy Data Space for Europe”.

9. Synergies, “Brief Description”.

10. DATA CELLAR, “About the project”.

11. TRUSTEE, “Welcome to the TRUSTEE project”.

12. Gaia-X, “Architecture Document 22.04 Release”.

13. CENELEC, “CEN-CENELEC-ETSI Smart Grid Coordination Group Smart Grid Reference Architecture”.

14. ENTSO-E, “The Harmonised Electricity Market Role Model”, 2022.

15. Connectathon Week 2024.

16. ENTSO-E, “ENTSO-E Research, Development, & Innovation Roadmap 2024-2034”, published: 10.07.2024.

17. European Commission, “NIFO - National Interoperability Framework Observatory”.

18. L. Hirth et al., “The ENTSO-E Transparency Platform: A review of Europe’s most ambitious electricity data platform”, Applied Economics, vol. 225, p. 1054, 2018.