Welcome to the ‘technical’ section of this knowledge base. This page contains resources related to the technical aspects of Data Spaces.
The topics in this section are based on the technical building blocks of the Data Spaces Support Centre Blueprint v1.0.
This page explains the technical building blocks in the Data Spaces Support Centre blueprint. This can help understand the different categories within this building block, which is especially helpful when navigating our own business topic page.
The dissertation explores the challenges users face in managing their privacy when using digital services, particularly focusing on the widespread but often disregarded cookie banners seen on EU websites. It proposes the development of Privacy Enhancing Tools (PETs) to empower users in controlling their personal data, merging insights from law, economics, and software development. Through six chapters, the research outlines a typology of control tasks users need to perform, identifies barriers they encounter, evaluates existing PET functionalities, and designs experimental tools to enhance privacy control, aiming to bridge the gap between legal rights and effective user empowerment in digital privacy.
This document outlines how Catena-X and the Smart Connected Supplier Network (SCSN) work together towards data space interoperability.
The text discusses the importance of data spaces and interoperability in unlocking the full potential of data sharing. It highlights challenges in semantic interoperability across data spaces due to varying vocabularies. The paper proposes using the Data Catalogue Vocabulary Application Profile (DCAT-AP) to standardize vocabulary exchange, aiming to enhance discoverability and facilitate federated searches across data spaces, ultimately supporting semantic interoperability.
Gaia-X developed a Trust Framework and Labelling Framework that safeguard data protection, transparency, security, portability, and flexibility for the ecosystem as well as sovereignty and European Control.
The Trust Framework is the set of rules that defines the minimum baseline to become part of the Gaia-X Ecosystem. These rules ensure a common governance and the basic levels of interoperability across individual ecosystems, while giving the users full control over their choices.
The Trust Framework uses verifiable credentials and linked data representation to build a FAIR knowledge graph of verifiable claims from which additional trust and composability indexes can be automatically computed.
This guide actively supports organisations with challenges regarding data sharing for AI applications. This guide focuses on the guidelines and building blocks to interconnect data spaces.
This guide actively supports organisations with challenges regarding data sharing for AI applications. In doing so, this guide focuses on the guidelines and building blocks for individual (sectoral, application-specific) AI data spaces.
