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Linked Data on theWeb and its Relationship with Distributed Ledgers (LDOW/LDDL)

Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review

Autorschaft

  • Maribel Acosta
  • Tim Berners-Lee
  • Anastasia Dimou
  • John Domingue
  • Maria-Esther Vidal

Organisationseinheiten

Externe Organisationen

  • Karlsruher Institut für Technologie (KIT)
  • W3C/MIT
  • Universiteit Gent
  • The Open University
  • University of Southampton
  • University of California at Santa Barbara
  • Technische Informationsbibliothek (TIB) Leibniz-Informationszentrum Technik und Naturwissenschaften und Universitätsbibliothek
  • Maastricht University
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Details

OriginalspracheEnglisch
Titel des SammelwerksWWW '19
UntertitelCompanion Proceedings of The 2019 World Wide Web Conference
Herausgeber/-innenLing Liu, Ryen White
ErscheinungsortNew York
Herausgeber (Verlag)Association for Computing Machinery (ACM)
Seiten823-839
ISBN (Print)9781450366755
PublikationsstatusVeröffentlicht - 13 Mai 2019

Abstract

Decentralised data solutions bring their own sets of capabilities, requirements and issues not necessarily present in centralised solutions. In order to compare the properties of different approaches or tools for management of decentralised data, it is important to have a common evaluation framework. We present a set of dimensions relevant to data management in decentralised contexts and use them to define principles extending the FAIR framework, initially developed for open research data. By characterising a range of different data solutions or approaches by how TRusted, Autonomous, Distributed and dEcentralised, in addition to how Findable, Accessible, Interoperable and Reusable, they are, we show that our FAIR TRADE framework is useful for describing and evaluating the management of decentralised data solutions, and aim to contribute to the development of best practice in a developing field.

Zitieren

Linked Data on theWeb and its Relationship with Distributed Ledgers (LDOW/LDDL). / Acosta, Maribel; Berners-Lee, Tim; Dimou, Anastasia et al.
WWW '19: Companion Proceedings of The 2019 World Wide Web Conference. Hrsg. / Ling Liu; Ryen White. New York: Association for Computing Machinery (ACM), 2019. S. 823-839.

Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review

Acosta, M, Berners-Lee, T, Dimou, A, Domingue, J, Ibáñez, L-D, Janowicz, K, Vidal, M-E & Zaveri, A 2019, Linked Data on theWeb and its Relationship with Distributed Ledgers (LDOW/LDDL). in L Liu & R White (Hrsg.), WWW '19: Companion Proceedings of The 2019 World Wide Web Conference. Association for Computing Machinery (ACM), New York, S. 823-839. https://doi.org/10.1145/3308560.3317072
Acosta, M., Berners-Lee, T., Dimou, A., Domingue, J., Ibáñez, L.-D., Janowicz, K., Vidal, M.-E., & Zaveri, A. (2019). Linked Data on theWeb and its Relationship with Distributed Ledgers (LDOW/LDDL). In L. Liu, & R. White (Hrsg.), WWW '19: Companion Proceedings of The 2019 World Wide Web Conference (S. 823-839). Association for Computing Machinery (ACM). https://doi.org/10.1145/3308560.3317072
Acosta M, Berners-Lee T, Dimou A, Domingue J, Ibáñez LD, Janowicz K et al. Linked Data on theWeb and its Relationship with Distributed Ledgers (LDOW/LDDL). in Liu L, White R, Hrsg., WWW '19: Companion Proceedings of The 2019 World Wide Web Conference. New York: Association for Computing Machinery (ACM). 2019. S. 823-839 doi: 10.1145/3308560.3317072
Acosta, Maribel ; Berners-Lee, Tim ; Dimou, Anastasia et al. / Linked Data on theWeb and its Relationship with Distributed Ledgers (LDOW/LDDL). WWW '19: Companion Proceedings of The 2019 World Wide Web Conference. Hrsg. / Ling Liu ; Ryen White. New York : Association for Computing Machinery (ACM), 2019. S. 823-839
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abstract = "Decentralised data solutions bring their own sets of capabilities, requirements and issues not necessarily present in centralised solutions. In order to compare the properties of different approaches or tools for management of decentralised data, it is important to have a common evaluation framework. We present a set of dimensions relevant to data management in decentralised contexts and use them to define principles extending the FAIR framework, initially developed for open research data. By characterising a range of different data solutions or approaches by how TRusted, Autonomous, Distributed and dEcentralised, in addition to how Findable, Accessible, Interoperable and Reusable, they are, we show that our FAIR TRADE framework is useful for describing and evaluating the management of decentralised data solutions, and aim to contribute to the development of best practice in a developing field.",
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AU - Dimou, Anastasia

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AU - Ibáñez, Luis-Daniel

AU - Janowicz, Krzysztof

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