McLachlan, S, Kyrimi, E, Dube, K, Fenton, N and Webley, LC (2022) Lawmaps: enabling legal AI development through visualisation of the implicit structure of legislation and lawyerly process. Artificial Intelligence and Law. ISSN 0924-8463

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Abstract

Modelling that exploits visual elements and information visualisation are important areas that have contributed immensely to understanding and the computerisation advancements in many domains and yet remain unexplored for the benefit of the law and legal practice. This paper investigates the challenge of modelling and expressing structures and processes in legislation and the law by using visual modelling and information visualisation (InfoVis) to assist accessibility of legal knowledge, practice and knowledge formalisation as a basis for legal AI. The paper uses a subset of the well-defined Unified Modelling Language (UML) to visually express the structure and process of the legislation and the law to create visual flow diagrams called lawmaps, which form the basis of further formalisation. A lawmap development methodology is presented and evaluated by creating a set of lawmaps for the practice of conveyancing and the Landlords and Tenants Act 1954 of the United Kingdom. This paper is the first of a new breed of preliminary solutions capable of application across all aspects, from legislation to practice; and capable of accelerating development of legal AI.

Item Type:	Article
Uncontrolled Keywords:	0801 Artificial Intelligence and Image Processing, 1702 Cognitive Sciences, 1801 Law
Subjects:	K Law > K Law (General) T Technology > T Technology (General)
Divisions:	Law
Publisher:	Springer
Date Deposited:	04 Feb 2022 12:27
Last Modified:	04 Feb 2022 12:30
DOI or ID number:	10.1007/s10506-021-09298-0
URI:	https://researchonline.ljmu.ac.uk/id/eprint/16233

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