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Shared Digital Twins: Data sovereignty in logistics networks

In: Data Science and Innovation in Supply Chain Management: How Data Transforms the Value Chain. Proceedings of the Hamburg International Conference of Logistics (HICL), Vol. 29

Author

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  • Haße, Hendrik
  • van der Valk, Hendrik
  • Weißenberg, Norbert
  • Otto, Boris

Abstract

Purpose: Digital Twins attract much attention in science and practice, because of their capability to integrate operational data from a wide variety of sources. Thus, providing a complete overview of an asset throughout its entire life cycle. This article develops and demonstrates a Digital Twin, which enables a sovereign and multilateral sharing of sensitive IoT data based on proven standards. Methodology: The design described in this paper is developed following the design science research methodology. Current challenges and solution objectives are derived from literature and the solution approach is implemented and demonstrated in a central artefact. The findings are evaluated and iterated back into the design of the central artefact. Findings: For multilateral data exchange of sensitive operational data, standards are needed that allow for interoperability of several stakeholders and for providing a secure and sovereign data exchange. Therefore, the designs of the Plattform Industrie 4.0 Asset Administration Shell and the International Data Spaces are merged in this contribution. In this way, Digital Twins can be used in cross-company network struc-tures. Originality: Multilateral data sharing is still associated with considerable security risks for the companies providing the data. Therefore, the consideration of data sovereignty aspects for Digital Twins is very limited. Furthermore, Digital Twins are seldom addressed in the context of cross-company data sharing.

Suggested Citation

  • Haße, Hendrik & van der Valk, Hendrik & Weißenberg, Norbert & Otto, Boris, 2020. "Shared Digital Twins: Data sovereignty in logistics networks," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Blecker, Thorsten & Ringle, Christian M. (ed.), Data Science and Innovation in Supply Chain Management: How Data Transforms the Value Chain. Proceedings of the Hamburg International Conference of Lo, volume 29, pages 763-795, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    • Handle: RePEc:zbw:hiclch:228939
    DOI: 10.15480/882.3119
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    References listed on IDEAS

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    1. Xi Vincent Wang & Lihui Wang, 2019. "Digital twin-based WEEE recycling, recovery and remanufacturing in the background of Industry 4.0," International Journal of Production Research, Taylor & Francis Journals, vol. 57(12), pages 3892-3902, June.
    2. Haße, Hendrik & Li, Bin & Weißenberg, Norbert & Cirullies, Jan & Otto, Boris, 2019. "Digital twin for real-time data processing in logistics," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Blecker, Thorsten & Ringle, Christian M. (ed.), Artificial Intelligence and Digital Transformation in Supply Chain Management: Innovative Approaches for Supply Chains. Proceedings of the Hamburg Int, volume 27, pages 4-28, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
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    1. Rantala, Tero & Ukko, Juhani & Nasiri, Mina & Saunila, Minna, 2023. "Shifting focus of value creation through industrial digital twins—From internal application to ecosystem-level utilization," Technovation, Elsevier, vol. 125(C).

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