Efficient compliance checking of RDF data

Robaldo, Livio; Pacenza, Francesco; Zangari, Jessica; Calegari, Roberta

doi:10.1093/logcom/exad034

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Efficient compliance checking of RDF data

Livio Robaldo

, Francesco Pacenza, Jessica Zangari, Roberta Calegari

Journal of Logic and Computation

Swansea University Author: Livio Robaldo

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DOI (Published version): 10.1093/logcom/exad034

Abstract

Automated compliance checking, i.e. the task of automatically assessing whether states of affairs comply with normative systems, has recently received a lot of attention from the scientific community, also as a consequence of the increasing investments in Artificial Intelligence technologies for the...

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Published in:	Journal of Logic and Computation
ISSN:	0955-792X 1465-363X
Published:	Oxford University Press (OUP)
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URI:	https://cronfa.swan.ac.uk/Record/cronfa63627
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first_indexed	2023-06-21T13:33:36Z
last_indexed	2023-06-21T13:33:36Z
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spelling	v2 63627 2023-06-13 Efficient compliance checking of RDF data b711cf9f3a7821ec52bd1e53b4f6cf9e 0000-0003-4713-8990 Livio Robaldo Livio Robaldo true false 2023-06-13 LAWD Automated compliance checking, i.e. the task of automatically assessing whether states of affairs comply with normative systems, has recently received a lot of attention from the scientific community, also as a consequence of the increasing investments in Artificial Intelligence technologies for the legal domain (LegalTech). The authors of this paper deem as crucial the research and implementation of compliance checkers that can directly process data in RDF format, as nowadays more and more (big) data in this format are becoming available worldwide, across a multitude of different domains. Among the automated technologies that have been used in recent literature, to the best of our knowledge, only two of them have been evaluated with input states of affairs encoded in RDF format. This paper formalizes a selected use case in these two technologies and compares the implementations, also in terms of simulations with respect to shared synthetic datasets. Journal Article Journal of Logic and Computation Oxford University Press (OUP) 0955-792X 1465-363X Automated compliance checking, AI technologies, RDF data 0 0 0 0001-01-01 10.1093/logcom/exad034 http://dx.doi.org/10.1093/logcom/exad034 COLLEGE NANME Law COLLEGE CODE LAWD Swansea University SU Library paid the OA fee (TA Institutional Deal) Livio Robaldo has been supported by the Legal Innovation Lab Wales operation within Swansea University's Hillary Rodham Clinton School of Law. The operation has been part-funded by the European Regional Development Fund through the Welsh Government. Francesco Calimeri, Francesco Pacenza, and Jessica Zangari acknowledge the support of the PNRR project FAIR - Future AI Research (PE00000013), Spoke 9 - Green-aware AI, under the NRRP MUR program funded by the NextGenerationEU, and the support of the project PRIN PE6, Title: Declarative Reasoning over Streams'', funded by the Italian Ministero dell'Università, dell'Istruzione e della Ri cerca (MIUR), CUP:H24I17000080001. The research of Roberta Calegari has been partially supported by the CompuLaw'' project, funded by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (Grant Agreement No. 833647). 2023-10-03T11:27:25.4721572 2023-06-13T11:34:33.6234870 Faculty of Humanities and Social Sciences Hilary Rodham Clinton School of Law Livio Robaldo 0000-0003-4713-8990 1 Francesco Pacenza 2 Jessica Zangari 3 Roberta Calegari 4 63627__27918__745a4a5f78d44da4a5ce7b711d86130a.pdf 63627.pdf 2023-06-21T14:49:33.7825735 Output 2978799 application/pdf Version of Record true © The Author(s) 2023. Published by Oxford University Press. Distributed under the terms of a Creative Commons Attribution 4.0 License (CC BY 4.0). true eng https://creativecommons.org/licenses/by/4.0/
title	Efficient compliance checking of RDF data
spellingShingle	Efficient compliance checking of RDF data Livio Robaldo
title_short	Efficient compliance checking of RDF data
title_full	Efficient compliance checking of RDF data
title_fullStr	Efficient compliance checking of RDF data
title_full_unstemmed	Efficient compliance checking of RDF data
title_sort	Efficient compliance checking of RDF data
author_id_str_mv	b711cf9f3a7821ec52bd1e53b4f6cf9e
author_id_fullname_str_mv	b711cf9f3a7821ec52bd1e53b4f6cf9e_***_Livio Robaldo
author	Livio Robaldo
author2	Livio Robaldo Francesco Pacenza Jessica Zangari Roberta Calegari
format	Journal article
container_title	Journal of Logic and Computation
institution	Swansea University
issn	0955-792X 1465-363X
doi_str_mv	10.1093/logcom/exad034
publisher	Oxford University Press (OUP)
college_str	Faculty of Humanities and Social Sciences
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hierarchy_top_id	facultyofhumanitiesandsocialsciences
hierarchy_top_title	Faculty of Humanities and Social Sciences
hierarchy_parent_id	facultyofhumanitiesandsocialsciences
hierarchy_parent_title	Faculty of Humanities and Social Sciences
department_str	Hilary Rodham Clinton School of Law{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}Hilary Rodham Clinton School of Law
url	http://dx.doi.org/10.1093/logcom/exad034
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description	Automated compliance checking, i.e. the task of automatically assessing whether states of affairs comply with normative systems, has recently received a lot of attention from the scientific community, also as a consequence of the increasing investments in Artificial Intelligence technologies for the legal domain (LegalTech). The authors of this paper deem as crucial the research and implementation of compliance checkers that can directly process data in RDF format, as nowadays more and more (big) data in this format are becoming available worldwide, across a multitude of different domains. Among the automated technologies that have been used in recent literature, to the best of our knowledge, only two of them have been evaluated with input states of affairs encoded in RDF format. This paper formalizes a selected use case in these two technologies and compares the implementations, also in terms of simulations with respect to shared synthetic datasets.
published_date	0001-01-01T11:27:27Z
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Efficient compliance checking of RDF data

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