Legal Knowledge Representation Using a Faceted Scheme

Author(s):  
Michelle Cumyn ◽  
Günter Reiner ◽  
Sabine Mas ◽  
David Lesieur
2021 ◽  
Author(s):  
Réka Markovich ◽  
Olivier Roy

Bill 25 proposed by the Texas Senate in 2017 was created to eliminate the so-called ‘wrongful birth’ cause of action. This plan raised some questions about the ‘right to know’ and indirectly about rights in general. We provide a preliminary logical analysis investigating these questions by using deontic and epistemic logics within the theory of normative positions. This work contributes to the logic-based legal knowledge representation tradition, and to the formal conceptual analysis of legal rights studying the cause of action’s role in the debated relation between the Hohfeldian categories ‘claim-right’ and ‘power’.


Author(s):  
Vytautas Čyras

Knowledge visualization (KV) and knowledge representation (KR) are distinguished, though both are knowledge management processes. Knowledge visualization is subject to humans, whereas knowledge representation – to 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.


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