Explainable Reasoning with Legal Big Data: A Layered Framework

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

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Explainable Reasoning with Legal Big Data: A Layered Framework

Livio Robaldo

, 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

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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

first_indexed	2022-07-11T13:58:09Z
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spelling	2022-12-21T16:00:18.2376452 v2 60445 2022-07-11 Explainable Reasoning with Legal Big Data: A Layered Framework b711cf9f3a7821ec52bd1e53b4f6cf9e 0000-0003-4713-8990 Livio Robaldo Livio Robaldo true false 2022-07-11 HRCL 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. Journal Article Journal of Applied Logics - IfCoLog Journal 9 4 College Publication 2631-9810 2631-9829 1 7 2022 2022-07-01 https://www.collegepublications.co.uk/ifcolog/?00056 https://www.collegepublications.co.uk/ifcolog/?00056 COLLEGE NANME Hillary Rodham Clinton Law School COLLEGE CODE HRCL Swansea University 2022-12-21T16:00:18.2376452 2022-07-11T14:49:43.5755708 Faculty of Humanities and Social Sciences Hilary Rodham Clinton School of Law Livio Robaldo 0000-0003-4713-8990 1 Grigoris Antoniou 2 Katie Atkinson 3 George Baryannis 4 Sotiris Batsakis 5 Luigi Di Caro 6 Guido Governatori 7 Giovanni Siragusa 8 60445__24533__c3edf861f4c3416895db31ef19e4ae9f.pdf Antoniou et al., 2022.pdf 2022-07-11T14:56:08.9581291 Output 345404 application/pdf Version of Record true This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. true eng http://creativecommons.org/licenses/by-nc-nd/4.0/
title	Explainable Reasoning with Legal Big Data: A Layered Framework
spellingShingle	Explainable Reasoning with Legal Big Data: A Layered Framework Livio Robaldo
title_short	Explainable Reasoning with Legal Big Data: A Layered Framework
title_full	Explainable Reasoning with Legal Big Data: A Layered Framework
title_fullStr	Explainable Reasoning with Legal Big Data: A Layered Framework
title_full_unstemmed	Explainable Reasoning with Legal Big Data: A Layered Framework
title_sort	Explainable Reasoning with Legal Big Data: A Layered Framework
author_id_str_mv	b711cf9f3a7821ec52bd1e53b4f6cf9e
author_id_fullname_str_mv	b711cf9f3a7821ec52bd1e53b4f6cf9e_***_Livio Robaldo
author	Livio Robaldo
author2	Livio Robaldo Grigoris Antoniou Katie Atkinson George Baryannis Sotiris Batsakis Luigi Di Caro Guido Governatori Giovanni Siragusa
format	Journal article
container_title	Journal of Applied Logics - IfCoLog Journal
container_volume	9
container_issue	4
publishDate	2022
institution	Swansea University
issn	2631-9810 2631-9829
publisher	College Publication
college_str	Faculty of Humanities and Social Sciences
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hierarchy_top_title	Faculty of Humanities and Social Sciences
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department_str	Hilary Rodham Clinton School of Law{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}Hilary Rodham Clinton School of Law
url	https://www.collegepublications.co.uk/ifcolog/?00056
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description	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.
published_date	2022-07-01T14:21:08Z
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Explainable Reasoning with Legal Big Data: A Layered Framework

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