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short-paper

Semantics in Dataspaces: Origin and Future Directions

Authors:

Johannes Theissen-Lipp,

Christoph Lange,

Alexander Paulus,

Edward CurryAuthors Info & Claims

WWW '23 Companion: Companion Proceedings of the ACM Web Conference 2023

Pages 1504 - 1507

https://doi.org/10.1145/3543873.3587689

Published: 30 April 2023 Publication History

Abstract

The term dataspace was coined two decades ago [12] and has evolved since then. Definitions range from (i) an abstraction for data management in an identifiable scope [15] over (iii) a multi-sided data platform connecting participants in an ecosystem [21] to (iii) interlinking data towards loosely connected (global) information [17]. Many implementations and scientific notions follow different interpretations of the term dataspace, but agree on some use of semantic technologies. For example, dataspaces such as the European Open Science Cloud and the German National Research Data Infrastructure are committed to applying the FAIR principles [11, 16]. Dataspaces built on top of Gaia-X are using semantic methods for service Self-Descriptions [13]. This paper investigates ongoing dataspace efforts and aims to provide insights on the definition of the term dataspace, the usage of semantics and FAIR principles, and future directions for the role of semantics in dataspaces.

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Cited By

Akbari Gurabi MHermsen FMandal ADecker S(2024)Towards Privacy-Preserving Machine Learning in Sovereign Data Spaces: Opportunities and ChallengesPrivacy and Identity Management. Sharing in a Digital World10.1007/978-3-031-57978-3_11(158-174)Online publication date: 23-Apr-2024
https://doi.org/10.1007/978-3-031-57978-3_11

Index Terms

Semantics in Dataspaces: Origin and Future Directions
1. Information systems
2. Theory of computation
  1. Semantics and reasoning

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cover image ACM Conferences

WWW '23 Companion: Companion Proceedings of the ACM Web Conference 2023

April 2023

1567 pages

ISBN:9781450394192

DOI:10.1145/3543873

Copyright © 2023 ACM.

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Publication History

Published: 30 April 2023

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Short-paper
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Refereed limited

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Digital Europe Programme
German Federal Ministry of Education and Research
German Federal Ministry of Transport and Digital Infrastructure
Deutsche Forschungsgemeinschaft
Science Foundation Ireland

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WWW '23

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SIGWEB

WWW '23: The ACM Web Conference 2023

April 30 - May 4, 2023

TX, Austin, USA

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Cited By

Akbari Gurabi MHermsen FMandal ADecker S(2024)Towards Privacy-Preserving Machine Learning in Sovereign Data Spaces: Opportunities and ChallengesPrivacy and Identity Management. Sharing in a Digital World10.1007/978-3-031-57978-3_11(158-174)Online publication date: 23-Apr-2024
https://doi.org/10.1007/978-3-031-57978-3_11

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