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The FAIR TRADE Framework for Assessing Decentralised Data Solutions

Domingue, John; Third, Allan and Ramachandran, Manoharan (2019). The FAIR TRADE Framework for Assessing Decentralised Data Solutions. In: WWW2019 workshop: Linked Data on the Web and its Relationship with Distributed Ledgers (LDOW/LDDL), 13 May 2019, San Francisco, USA, (In Press).

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DOI (Digital Object Identifier) Link: https://doi.org/10.1145/3308560.3317076
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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.

Item Type: Conference or Workshop Item
Copyright Holders: 2019 Companion Proceedings of the 2019 World Wide Web Conference
Keywords: distributed data; evaluation; open data; semantic blockchain
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
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Item ID: 60149
Depositing User: Manoharan Ramachandran
Date Deposited: 15 Apr 2019 08:37
Last Modified: 02 May 2019 11:54
URI: http://oro.open.ac.uk/id/eprint/60149
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