Abstract
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.
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Hellmanzik, B., Sandkuhl, K. (2023). A Data Value Matrix: Linking FAIR Data with Business Models. In: Nurcan, S., Opdahl, A.L., Mouratidis, H., Tsohou, A. (eds) Research Challenges in Information Science: Information Science and the Connected World. RCIS 2023. Lecture Notes in Business Information Processing, vol 476. Springer, Cham. https://doi.org/10.1007/978-3-031-33080-3_41
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DOI: https://doi.org/10.1007/978-3-031-33080-3_41
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