SmaRT visualisation of legal rules for compliance
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Published Version
Date
2018-01-17
Authors
Seppälä, Selja
Ceci, Marcello
Huang, Hai
O'Brien, Leona
Butler, Tom
Journal Title
Journal ISSN
Volume Title
Publisher
CEUR Workshop Proceedings
Published Version
Abstract
This paper presents a visualization technique to assist legal experts in formalising their interpretation of legal texts in terms of regulatory requirements. (Semi-)automation of compliance processes requires a machine-readable version of legal requirements in a format that enables effective compliance assessment. The use of a semi-structured controlled natural language as an intermediate step of the translation from a human-readable text to a machine-readable and understandable format ensures that the process of interpretation of those requirements is as simple as possible. However, it does not ensure that the formal representation resulting from the interpretation faithfully represents the intended semantics provided by the legal expert. Visualization techniques such as property graphs in Neo4j could fill this gap, allowing legal experts to understand and control the formal representation of the result of their act of interpretation.
Description
Keywords
SBVR , RegTech , Controlled natural languages , Neo4j
Citation
Seppälä, S., Huang, H. and Ceci, M. (2017) ‘SmaRT visualisation of legal rules for compliance’, Proceedings of the 1st Workshop on Technologies for Regulatory Compliance, Luxembourg, 13 December, CEUR Workshop Proceedings, Vol-2049, pp. 73-85. Available at: http://ceur-ws.org/Vol-2049/08paper.pdf (Accessed: 2 September 2021)