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Auflistung nach Schlagwort "data sovereignty"

1 - 2 von 2
  • Konferenzbeitrag
    Data sovereignty needs in agricultural use cases
    (43. GIL-Jahrestagung, Resiliente Agri-Food-Systeme, 2023) Boye, Frederik; Matar, Raghad; Neuschwander, Philipp
    With today's shift towards digital farming, data transfer and processing are becoming increasingly essential for optimizing farm operations. In the complex arable farming sector, there exist numerous use cases involving a variety of actors and processes. Designing new digital ecosystems, such as agricultural data spaces that support existing workflows while enabling new opportunities for data-driven services, requires a good understanding of existing processes and data sovereignty needs. In this paper, we categorize data exchange use cases in arable farming and analyze the respective data sovereignty needs for each category. The results of our contribution can be used as a basis for further analysis and evaluation of data-sharing approaches in terms of their suitability for meeting different data sovereignty needs in agriculture, as well as in the process of requirements analysis when designing such systems.
  • Konferenzbeitrag
    Trustworthy Data Exchange: Leveraging Linked Data for Enhanced IDS Certification
    (INFORMATIK 2024, 2024) Hackel, Sascha; Makohl, Marie-Elisabeth; Petrac, Simon
    In today’s data-driven business environments, ensuring secure and controlled data sharing is essential. However, existing solutions often lack mechanisms to maintain data sovereignty and establish trust among ecosystem participants. This paper presents a novel approach to the establishment of International Data Spaces (IDS) certification, focusing on the use of a formal information model and Linked Data. The proposed certification framework leverages the formal information model to define the structure and semantics of the certification process. It enables machine-recognizable data representations, ensuring interoperability and facilitating automated processing of certification information. Using Linked Data principles, the framework provides an exact description of system capabilities and requirements. This increases transparency and facilitates more reliable and trustworthy data exchange within IDS.