How open and restricted data can coexist in a Data Space

A Data Space is a digital environment that enables the reliable exchange of data while retaining sovereignty and ensuring trust and security under a set of mutually agreed rules. While in Spatial Data Infrastructures (SDI) the focus was on providers opening their data to everybody, in Data Spaces the focus is on a more symmetrical and distributed data exchange among participants. These are specifically designed for sharing restricted or sensitive data, respecting privacy and supporting private companies in the digital economy.

The European Commission is promoting the creation of up to 15 common European Data Spaces that are expected to bring together relevant data infrastructure and governance frameworks in strategic sectors as part of the European Strategy for Data. The aim is to face global challenges and overcome legal and technical barriers to data sharing by combining the necessary tools and services in an interoperable and reusable way. Among these, the Green Deal Data Space (GDDS) supports the Green Deal priority actions in terms of sharing high value and high quality datasets for biodiversity preservation, zero pollution, circular economy, climate change mitigation, deforestation reduction, smart mobility and environmental compliance.

Most environmental data within GDDS originates from public administrations and is mainly open, except for GDPR-protected or sensitive species data. However, data from commercial activities—such as soil markets, farming, and textile recycling—is considered proprietary and therefore restricted. The GDDS should be designed and built respecting European values and applying FAIR principles (Findable, Accessible, Interoperable, Reusable). It is also a goal to interconnect fragmented and cross-domain data from public and private sectors, as well as citizen-generated sources, while maintaining a balance between open and restricted data. This communication explores how SDI fundamentals for open data can be combined with Data Space technologies for restricted data, ensuring the interests of all actors.

The architecture initially adopted by the GDDS is based on a piece of software called “data space connector” that follows standards defined by the International Data Space Association. The connector is providing access to restricted data based on traditional authentication or a Decentralized Claims Protocol system complemented by digital contracts. Only authorized actors can use the data. In SAGE, we are also using this architecture to share open data coming from APIs.

Due to the heterogeneous nature of data in the GDDS, the precise understanding of the meaning of this data is of a paramount importance. Thus, semantics and well-known ontologies play an important role in Data Spaces. In SAGE, we propose to use Essential Variables (EVs) as a common language to describe data. Previous work has been done in AD4GD in using Essential Biodiversity Variables together with I-ADOPT ontology framework for metadata and data description. This work will be expanded with the rest of EVs facilitating breaking the silos among data domains.    

This research is conducted in SAGE project co-funded by the European Union from the Digital Europe Programme (DIGITAL) under grant agreement Nº 101195471 and some parts were initiated under AD4GD EC HORIZON.2.6 project (Nº 101061001).