Designing Data Spaces

1. Use Cases and Data Ecosystems

   1. Agricultural Data Space

      • Ralf Kalmar, Bernd Rauch, Jörg Dörr, Peter Liggesmeyer

      Pages 279-290Open Access

   2. Medical Data Spaces in Healthcare Data Ecosystems

      • Thomas Berlage, Carsten Claussen, Sandra Geisler, Carlos A. Velasco, Stefan Decker

      Pages 291-311Open Access

   3. Industrial Data Spaces

      • Thomas Usländer, Andreas Teuscher

      Pages 313-327Open Access

   4. Energy Data Space

      • Volker Berkhout, Carsten Frey, Philipp Hertweck, David Nestle, Manuel Wickert

      Pages 329-341Open Access

   5. Mobility Data Space

      • Sebastian Pretzsch, Holger Drees, Lutz Rittershaus

      Pages 343-361Open Access

2. Solutions and Applications

   1. Front Matter

      Pages 363-363

      PDF

   2. Data Sharing Spaces: The BDVA Perspective

      • Edward Curry, Tuomo Tuikka, Andreas Metzger, Sonja Zillner, Natalie Bertels, Charlotte Ducuing et al.

      Pages 365-382Open Access

   3. Data Platform Solutions

      • Fabrice Tocco, Laurent Lafaye

      Pages 383-393Open Access

   4. FIWARE for Data Spaces

      • Ulrich Ahle, Juan Jose Hierro

      Pages 395-417Open Access

   5. Sovereign Cloud Technologies for Scalable Data Spaces

      • Wieland Holfelder, Andreas Mayer, Thomas Baumgart

      Pages 419-436Open Access

   6. Data Space Based on Mass Customization Model

      • Lucheng Chen, Haiqin Xie, Wen Yang, Lin Xiao

      Pages 437-450Open Access

   7. Huawei and International Data Spaces

      • Martin A. O’Brien, David Mohally, Götz P. Brasche, Andrea G. Sanfilippo

      Pages 451-469Open Access

   8. International Collaboration Between Data Spaces and Carrier Networks

      • Akira Sakaino

      Pages 471-483Open Access

   9. From Linear Supply Chains to Open Supply Ecosystems

      • Fabian Biegel, Nemrude Verzano

      Pages 485-492Open Access

   10. Data Spaces: First Applications in Mobility and Industry

       • Christoph Schlueter Langdon, Karsten Schweichhart

       Pages 493-511Open Access

   11. Competition, Security, and Transparency: Data in Connected Vehicles

       • Karsten Schulze

       Pages 513-520Open Access

   12. Data Space Functionality

       • Douwe Lycklama

       Pages 521-534Open Access

   13. The Energy Data Space: The Path to a European Approach for Energy

       • Martine Gouriet, Hervé Barancourt, Marianne Boust, Philippe Calvez, Michael Laskowski, Anne-Sophie Taillandier et al.

       Pages 535-575Open Access

3. Back Matter

   Pages 577-580

   PDF

This open access book provides a comprehensive view on data ecosystems and platform economics from methodical and technological foundations up to reports from practical implementations and applications in various industries.

To this end, the book is structured in four parts: Part I “Foundations and Contexts” provides a general overview about building, running, and governing data spaces and an introduction to the IDS and GAIA-X projects. Part II “Data Space Technologies” subsequently details various implementation aspects of IDS and GAIA-X, including eg data usage control, the usage of blockchain technologies, or semantic data integration and interoperability. Next, Part III describes various “Use Cases and Data Ecosystems” from various application areas such as agriculture, healthcare, industry, energy, and mobility. Part IV eventually offers an overview of several “Solutions and Applications”, eg including products and experiences from companies like Google, SAP, Huawei, T-Systems, Innopay and many more.

Overall, the book provides professionals in industry with an encompassing overview of the technological and economic aspects of data spaces, based on the International Data Spaces and Gaia-X initiatives. It presents implementations and business cases and gives an outlook to future developments. In doing so, it aims at proliferating the vision of a social data market economy based on data spaces which embrace trust and data sovereignty.

• Open Access
• Data Spaces
• GAIA-X
• Data Lakes
• Big Data
• Information Retrieval
• Information Systems Applications
• Data Ecosystems
• Data Integration
• Data Security

• Fraunhofer-Institut für Software- und Systemtechnik ISST, Dortmund, Germany

  Boris Otto

• Fraunhofer-Institut für Materialfluss und Logistik IML, Dortmund, Germany

  Michael ten Hompel

• Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS, Sankt Augustin, Germany

  Stefan Wrobel

Boris Otto is the Executive Director of the Fraunhofer Institute for Software and Systems Engineering ISST in Dortmund as well as Chair for Industrial Information Management at TU Dortmund. His career path includes the University of St. Gallen, PricewaterhouseCoopers, SAP, and the Fraunhofer Institute for Industrial Engineering IAO. He is a member of the boards of directors of the Gaia-X, European Association for Data and Cloud, AISBL and the International Data Spaces Association (IDSA). His research focuses on the fields of industrial information management, business and logistics networks, and methods for the design of digital business solutions.

Michael ten Hompel holds the Chair of Materials Handling and Warehousing at TU Dortmund and is Managing Director at Fraunhofer-Institute of Material Flow and Logistics IML. Besides his work as scientist, he also worked as entrepreneur and eg founded GamBit GmbH in Dortmund in 1988 and is still on the supervisory board of several logistics companies. He was also awarded the Innovationspreis NRW (Innovation Award North Rhine-Westphalia) in 2020.

Stefan Wrobel is Professor of Computer Science at U Bonn and Director of the Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS. His work is focused on questions of the digital revolution, in particular intelligent algorithms and systems for the large-scale analysis of data and the influence of Big Data/Smart Data on the use of information in companies and society. He was honored by the Gesellschaft für Informatik (German Informatics Society) as one of the formative minds in German AI history.