Year: 2025
Type: article
Abstract: Data spaces are collaborative environments where data is exchanged across organizations with agreed-upon rules, and they are emerging as crucial infrastructures for secure and efficient data sharing in the digital economy. This paper provides a comprehensive analysis of various prominent European data space architectures, specifically IDS-RAM, Gaia-X, FIWARE, and IHAN, using a structured methodology to evaluate their characteristics, strengths, and limitations. In addition, recommendations for enhancing security protocols and privacy protection mechanisms are proposed, which are essential for building trust in data sharing environments. Finally, advancements in current frameworks are identified, along with a set of proposed extension requirements designed to enhance the capabilities of data spaces. These suggestions focus on the need for standardized governance, improved interoperability, and mechanisms to ensure data sovereignty and ethical use. By addressing these areas, the paper aims to support the development of more robust data-sharing infrastructures that can adapt to the evolving landscape of data management, with a strong focus on maintaining the highest standards of security and privacy protection.
Source: Data Science and Engineering
Authors: Ashneet Khandpur Singh, Marcel Ortiz Sánchez, Marc Garnica Caparros, Mario Reyes de los Mozos, Silvia Castellvi, Simon Dalmolen, Kosmas Tsiakas, Paschalis Itsios, Ioannis Mariolis, Dimitrios Giakoumis, Silvia Rodríguez, Asier Aguayo Velasco, Daniel Cabello, Borja Perez Lopez
Language: English
Topic: Big Data and Digital Economy
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,390
Award: G740838408
OpenAlex ID: W4416196589