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2017
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13 pages
1 file
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.
2018
The law appears in legal texts and in typed legal situations. Textuality began to dominate with the reception of Roman law. The advancement of socially and legally used machines will decrease the importance of textuality and increase that of legal programming. Legal visualization fits this trend. The peculiarities of law form an object of visualization. Legal texts are in an abstract frame, which is not linguistically structured. Besides the types of legal situations, the pre-textual interdependencies of legal terms should be made visible. Situations can be governed by legal machines.
Informatica, 2015
This paper investigates an approach which is called structural legal visualization (SLV). It is about diagrammatical views which facilitate comprehension of the meaning of legal contents. Complexity reduction is a motive. An issue is the complexity of the entire legal system and the layman's limited ability to understand legal institutions and the millions of documents. A sequence of views in SLV can be compared with a narrative. SLV differs from information visualization and knowledge visualization. SLV relates to a scenario-centered graphical narrative rather than information display or user interfaces. SLV is about the generation (synthesis) of diagrams. The sequence of images depends on the user's goals. Different pathways through the informational space are concerned. With respect to an object's change or non-change, two variations of SLV are identified: dynamic SLV and static SLV. The latter is divided into two: incremental SLV and alternate focuses SLV.
Frontiers in Artificial Intelligence and Applications
This paper explores the subject matter of legal informatics. The life-long work of the first author concerning the visualization and coding of statutes is generalized. Besides positive law and customary law, the emergence of machine law is a current topic of focus in the literature. In machine law, legal acts are posited by machines and not by humans (primarily in a situational context). The transformation of a legal act to a legal document can happen in two ways. First, it is a transformation of the legal act into explicit punctuation, for example, for announcement in the case of laws or for written execution in the case of judgments, and, second, as a trend towards electronic documents. Legal theory forms a meta-level to the law and similarly legal informatics forms a meta-level to legal information. Legal informatics in Austria is based on the work of Ota Weinberger, Ilmar Tammelo and Leo Reisinger and has been developed by Erich Schweighofer in the framework of the IRIS conferen...
1993
Abstract Legal KBSs are based on knowledge contained in legal texts such as legislation, regulations and case histories and the practice of domain experts charged with operationalising this legislation. Legal texts and their opertionalisation can be analysed using textual analysis tools which lead to the production of a rule base which can be manipulated to establish a desired goal.
Artificial Intelligence and Law, 2022
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...
CEUR Proceedings, 2020
There has been an increase use of Domain-Specific Visual Modeling Language (DSVML) as a means of improving models' comprehensibility and, consequently, stakeholders' productivity. Combining the benefits of DSVMLs and of an ontological approach for designing and evaluating DSVMLs, we present, in this paper, the first-steps towards an ontology-based DSVML in the legal domain called LawV. The main purpose of LawV is to provide for a visual symbolic representation for legal statements. LawV has been built by applying an ontology-based language engineering method called PoNTO-S and UFO-L, a legal core ontology. To evaluate LawV, we instantiate a judicial case selected from the database of Appeal Court of the Espírito Santo State in Brazil.
Knowledge visualization (KV) and knowledge representation (KR) are distinguished, though both are knowledge management processes. Knowledge visualization is subject to humans, whereas knowledge representationto computers. In computing, knowledge representation leverages reasoning of software agents. Thus, KR is a branch of artificial intelligence. The subject matter of KR is representation methods. They are classified into (1) knowledge level and symbol level representations; (2) procedural and declarative representations; (3) logic-based, rule-based, frame-or object-based representations (supporting inference by inheritance); and (4) semantic networks. In legal informatics, methods of legal knowledge representation (LKR) are dealt with. An essential feature of LKR is the representation of deep knowledge, which is mainly tacit. It is easily understood by professional jurists and hardly by amateurs from outside law. This knowledge comprises the teleology of law and a whole implicit framework of legal system. The paper focuses on (1) identifying key features of KV and KR in the legal domain; and (2) distinguishing between visualization, symbolization, formalisation and mind mapping.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Law - ICAIL '13, 2013
This paper describes the development of prototype software-based tools for visualizing definitions within legal contracts. The tools demonstrate visualization techniques for enhancing the readability and comprehension of definitions and their associated characteristics. This contributes to more accurate and efficient drafting or reading of contracts through the exploration of the meaning and use of definitions including via word clouds, multilayer navigation, adjacency matrix and graph tree representations.
2013
This paper describes the development of prototype software-based tools for visualizing definitions within legal contracts. The tools demonstrate visualization techniques for enhancing the readability and comprehension of definitions and their associated characteristics. This contributes to more accurate and efficient drafting or reading of contracts through the exploration of the meaning and use of definitions including via word clouds, multilayer navigation, adjacency matrix and graph tree representations.
Law and Philosophy Library, 2014
This paper reviews visualizations in legal informatics. We focus on the transition from traditional rule-based linear textual representation such as "if A then B" to twoand threedimensional ones and films. A methodology of visualization with the thought pattern of tertium comparationis can be attributed to Arthur Kaufmann. A tertium visualization aims at a mental bridge between different languages. We explore how visualizations are constructed and what types can be found here. Review criteria comprise comprehension, relations, vertical-horizontal arrangement, time-space structure, the focus of attention, education, etc. Pictures for review are selected from JURIX 2012 proceedings. We conclude that making visualizations as avant-garde as JURIX projects themselves is a tough task that requires knowledge of law, computing, media and semiotics.
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