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A data value matrix: Linking FAIR data with business models
University of Rostock, Rostock, Germany.
Jönköping University, School of Engineering, JTH, Department of Computer Science and Informatics. University of Rostock, Rostock, Germany.ORCID iD: 0000-0002-7431-8412
2023 (English)In: Research Challenges in Information Science: Information Science and the Connected World17th International Conference, RCIS 2023, Corfu, Greece, May 23–26, 2023, Proceedings / [ed] S. Nurcan, A. L. Opdahl, H. Mouratidis & A. Tsohou, Cham: Springer, 2023, p. 585-592Conference paper, Published paper (Refereed)
Abstract [en]

Data is the raw material of digitization, but its economic use and potential economic benefits are not always clear. Therefore, we would like to show that the processing of data, especially according to FAIR principles, plays an enormous role in enabling business models and improving existing business models. This is being tested within the EU funded project Marispace-X, part of the Gaia-X initiative. The maritime domain in particular currently still suffers from a lack of digitization: while as much data is being collected as ever before, this data is often kept in silos and hardly reused or even shared. This work therefore involved linking the FAIR principles to a data value chain, which together with business model dimensions form a data value matrix. This application of this matrix was carried out together with practice partners using the example of maritime data processing in the use case “offshore wind” and can be used and adapted as an analysis tool for data-driven business models.

Place, publisher, year, edition, pages
Cham: Springer, 2023. p. 585-592
Series
Lecture Notes in Business Information Processing, ISSN 1865-1348, E-ISSN 1865-1356 ; 476
Keywords [en]
business model, Data value chain, dataspace, FAIR, Data handling, Economic and social effects, Matrix algebra, Business models, Data space, Data values, Digitisation, Economic potentials, Economic use, Value chains, Value matrixes, Offshore oil well production
National Category
Information Systems
Identifiers
URN: urn:nbn:se:hj:diva-63357DOI: 10.1007/978-3-031-33080-3_41Scopus ID: 2-s2.0-85163385364ISBN: 9783031330797 (print)ISBN: 9783031330803 (electronic)OAI: oai:DiVA.org:hj-63357DiVA, id: diva2:1828123
Conference
17th International Conference, RCIS 2023, Corfu, Greece, May 23–26, 2023
Available from: 2024-01-16 Created: 2024-01-16 Last updated: 2024-01-16Bibliographically approved

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Sandkuhl, Kurt

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