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@PHDTHESIS{TheissenLipp:995165,
      author       = {Theissen-Lipp, Johannes},
      othercontributors = {Decker, Stefan Josef and Quix, Christoph and Curry, Edward},
      title        = {{S}emantic foundations of dataspaces},
      school       = {RWTH Aachen University},
      type         = {Dissertation},
      address      = {Aachen},
      publisher    = {RWTH Aachen University},
      reportid     = {RWTH-2024-09760},
      pages        = {1 Online-Ressource : Illustrationen},
      year         = {2024},
      note         = {Veröffentlicht auf dem Publikationsserver der RWTH Aachen
                      University; Dissertation, RWTH Aachen University, 2024},
      abstract     = {Digital transformation is rapidly reshaping industries,
                      organizations, and societies around the world, driven by the
                      exponential growth of data from the Internet and the Web.
                      This data, encompassing both open and closed resources,
                      drives innovation and provides competitive advantages.
                      However, there is a growing demand for data sovereignty,
                      where individuals and organizations control their data
                      throughout its lifecycle. Initiatives such as dataspaces,
                      funded with €4-6 billion in Europe, and the Internet of
                      Production focus on data autonomy and integration, but
                      interoperability and common understanding remain critical
                      challenges. The fields of Semantic Web technologies and FAIR
                      data provide frameworks for addressing these challenges.
                      These semantic technologies enable seamless data exchange
                      and meaningful interpretation to maximize the potential of
                      data, yet they are not sufficiently utilized in dataspaces.
                      This thesis explores the semantic foundations of dataspaces,
                      aiming to integrate semantic technologies to improve data
                      interoperability and facilitate common understanding among
                      stakeholders. It also advances semantic technologies to
                      enhance their impact. This work proposes new concepts,
                      principles, best practices, and solutions to improve data
                      management in dataspaces. The key contributions of this
                      thesis include:- A Tailored Data Lifecycle Model for
                      Dataspaces: This model addresses the unique challenges and
                      requirements of dataspaces, ensuring a streamlined and
                      structured approach to managing data and metadata throughout
                      their lifecycle.- Principles of Information Models: These
                      models define a common core in dataspaces, providing a
                      structured representation of data, services, participants,
                      and interactions, and serving as a foundation for data
                      sovereignty and interoperability mechanisms.- Extended Data
                      Access Principles: These principles cover various types of
                      heterogeneity, improving data accessibility by managing
                      resource constraints, handling dynamic data changes, and
                      providing rich metadata to increase the quantity and quality
                      of information in dataspaces.- Methods for Improving Common
                      Domain Understanding: This includes techniques for
                      identification, best practices for vocabulary development,
                      involvement of non-experts, effective recommendation
                      systems, evolution of semantic information over time, and
                      improved validation techniques to enhance data
                      interoperability and (re)use in dataspaces. By combining
                      these contributions, this thesis confidently integrates
                      semantic technologies into dataspaces. This integration
                      enhances data and service interoperability and facilitates
                      common understanding within these environments, promoting
                      proper data management and reuse throughout the data
                      lifecycle. Our work provides valuable insights into the
                      effective management of information within the digital
                      ecosystem of dataspaces, contributing to the advancement of
                      knowledge in today's data-driven digital transformation.},
      cin          = {124510 / 120000},
      ddc          = {004},
      cid          = {$I:(DE-82)124510_20160614$ / $I:(DE-82)120000_20140620$},
      pnm          = {WS-A.II - Conceptual Foundations of Digital Shadows
                      (X080067-WS-A.II) / WS-A.I - Physical Infrastructure
                      Supporting Digital Shadows (X080067-WS-A.I) / DFG project
                      G:(GEPRIS)390621612 - EXC 2023: Internet of Production (IoP)
                      (390621612) / DFG project G:(GEPRIS)442146713 - NFDI4Ing –
                      Nationale Forschungsdateninfrastruktur für die
                      Ingenieurwissenschaften (442146713)},
      pid          = {G:(DE-82)X080067-WS-A.II / G:(DE-82)X080067-WS-A.I /
                      G:(GEPRIS)390621612 / G:(GEPRIS)442146713},
      typ          = {PUB:(DE-HGF)11},
      doi          = {10.18154/RWTH-2024-09760},
      url          = {https://publications.rwth-aachen.de/record/995165},
}