We investigate decision support systems and legal expert systems to represent the semantics of legal norms. The focus is twofold: Design and software-technical implementation of a comprehensive system to support model based reasoning on legal norms and enabling end-users to create, maintain, and analyze semantic models, i.e. ontologies, representing structure and semantics of norms.
A model based expression language (MxL) has been developed to coherently support the formalization of logical and arithmetical operations. MxL is intended to define complex, nested, strongly-typed, and functional operations. The paper summarizes research on the design and implementation of a legal expert system built upon model based decision structures. Thereby, three different components, namely a model store, a model execution component, and an interaction component have been developed. The formalization, execution, and analysis is analyzed on German child benefit regulations.
The formalization of normative texts, regarding to various aspects, e.g., propositional, deontological, temporal, defeasible, etc., is well studied. The generated insights have led to valuable principles allowing complex formal reasoning on given laws or contracts. The execution of algorithmically processable formalizations requires the translation of the textual representation, which is a complex and manual task. Advances in natural language processing have at most led to tools or algorithms supporting end-users during analysis, interpretation, and application of legal rules. The user perspective during the formalization process of legal rules has earned rather less attention within the last decades. Higher attention has user-enabled formalization of arguments drawn.
This ignorance of the users' perspective is counter-intuitive since the success of computer science and informatics is not at least determined by its applicability. The present digitization underpins this argument. This work investigates end-user centered legal reasoning. The focus is on specifying a domain specific language (DSL) enabling users to collaboratively define executable semantics of norms, and create isomorphic representations of the normative text. These representations are beneficial for creating, interpreting, and applying those norms. However, the creation of isomorphic representations remains complex and knowledge-intensive.