Discovering data spaces: A classification of design options

Technical coordination between organizations and security concerns are among the major barriers to data sharing. Data spaces are an emerging digital infrastructure that helps address these challenges by sovereignly sharing data across institutional boundaries. The data space concept is at the core of many high-profile research initiatives in the European Union and receives great adoption in practice. Despite the great interest, there is, however, a demand for more conceptual clarity and approaches to describe and design them purposefully. We propose a taxonomy of data space design options grounded in a literature review, an analysis of real-world objects, and over nine hours of expert interviews with data space initiatives. The taxonomy advances our understanding of data space designs and gives a framework to practice making informed design decisions. Our work provides a comprehensive solution space for data space designers to (a) (re-)design data spaces more efficiently and (b) acquire a ‘big picture’ of what needs to be considered. • Taxonomy of key characteristics to describe, classify, and redesign data spaces. • Grounded in literature review, analysis of real-world objects, and expert interviews. • Advances understanding of data space designs by providing a framework for informed design decisions. • Addresses the need for enhanced conceptual clarity and effective design tools for data spaces. • Illustrates the wide application of data spaces in various industries.

Authors

Institutions

Publication Details

Journal
Computers in Industry
Published
2024-11-15
DOI
https://doi.org/10.1016/j.compind.2024.104212
Citations
12
Primary Topic
Innovative Approaches in Technology and Social Development
Type
article
Field-Weighted Citation Impact
8.77

Funders

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article

Discovering data spaces: A classification of design options

ILANA GUR, Thorsten Schoormann, Frederik Möller, Anna Gieß
12 citations
Computers in Industry
Innovative Approaches in Technology and Social Development
8.77
article

Discovering data spaces: A classification of design options

ILANA GUR, Thorsten Schoormann, Frederik Möller, Anna Gieß
article en
12 citations

Abstract

Technical coordination between organizations and security concerns are among the major barriers to data sharing. Data spaces are an emerging digital infrastructure that helps address these challenges by sovereignly sharing data across institutional boundaries. The data space concept is at the core of many high-profile research initiatives in the European Union and receives great adoption in practice. Despite the great interest, there is, however, a demand for more conceptual clarity and approaches to describe and design them purposefully. We propose a taxonomy of data space design options grounded in a literature review, an analysis of real-world objects, and over nine hours of expert interviews with data space initiatives. The taxonomy advances our understanding of data space designs and gives a framework to practice making informed design decisions. Our work provides a comprehensive solution space for data space designers to (a) (re-)design data spaces more efficiently and (b) acquire a ‘big picture’ of what needs to be considered. • Taxonomy of key characteristics to describe, classify, and redesign data spaces. • Grounded in literature review, analysis of real-world objects, and expert interviews. • Advances understanding of data space designs by providing a framework for informed design decisions. • Addresses the need for enhanced conceptual clarity and effective design tools for data spaces. • Illustrates the wide application of data spaces in various industries.

Computers in IndustryVol. 164
Fraunhofer Institute for Software and Systems Engineering (DE), Technische Universität Braunschweig (DE)
Bundesministerium für Bildung und Forschung, Bundesministerium für Bildung, Wissenschaft, Forschung und Technologie
Openalex Percentile: Top 2%
Innovative Approaches in Technology and Social Development
8.77
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Discovering data spaces: A classification of design options — ILANA GUR, Thorsten Schoormann, et al. · Computers in Industry (2024) | TGRS Research Map | TGRS