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Title: Shared Digital Twins : data sovereignty in logistics networks
Language: English
Authors: Haße, Hendrik 
van der Valk, Hendrik 
Weißenberg, Norbert 
Otto, Boris 
Editor: Kersten, Wolfgang 
Blecker, Thorsten 
Ringle, Christian M.  
Keywords: logistics;industry 4.0;digitalization;innovation;supply chain management;artificial intelligence;Data science
Issue Date: 23-Sep-2020
Publisher: epubli
Source: Hamburg International Conference of Logistics (HICL) 29: 763-795 (2020)
Part of Series: Proceedings of the Hamburg International Conference of Logistics (HICL) 
Volume number: 29
Abstract (english): 
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 multilat-eral 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 de-rived 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 se-cure 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 sov-ereignty aspects for Digital Twins is very limited. Furthermore, Digital Twins are sel-dom addressed in the context of cross-company data sharing.
Conference: Hamburg International Conference of Logistics (HICL) 2020 
DOI: 10.15480/882.3119
ISBN: 978-3-753123-46-2
ISSN: 2365-5070
Document Type: Chapter/Article (Proceedings)
License: CC BY-SA 4.0 (Attribution-ShareAlike 4.0) CC BY-SA 4.0 (Attribution-ShareAlike 4.0)
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