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Explainable Reasoning with Legal Big Data: A Layered Framework

Livio Robaldo Orcid Logo, Grigoris Antoniou, Katie Atkinson, George Baryannis, Sotiris Batsakis, Luigi Di Caro, Guido Governatori, Giovanni Siragusa

Journal of Applied Logics - IfCoLog Journal, Volume: 9, Issue: 4

Swansea University Author: Livio Robaldo Orcid Logo

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Abstract

Knowledge representation and reasoning in the legal domain has primarily focused on case studies where knowledge and data can fit in main memory. However, this assumption no longer applies in the era of big data, where large amounts of data are generated daily. This paper discusses new opportunities...

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Published in: Journal of Applied Logics - IfCoLog Journal
ISSN: 2631-9810 2631-9829
Published: College Publication 2022
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa60445
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Abstract: Knowledge representation and reasoning in the legal domain has primarily focused on case studies where knowledge and data can fit in main memory. However, this assumption no longer applies in the era of big data, where large amounts of data are generated daily. This paper discusses new opportunities and challenges that emerge in relation to reasoning with legal big data and the concepts of volume, velocity, variety and veracity. A four-layer legal big data framework is proposed to manage the complete lifecycle of legal big data from sourcing, processing and storage, to reasoning, analysis and consumption. Within each layer, a number of relevant future research directions are also identified, which can facilitate the realisation of knowledge-rich legal big datasolutions.
Item Description: https://www.collegepublications.co.uk/ifcolog/?00056
College: Faculty of Humanities and Social Sciences
Issue: 4

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