Master's Thesis Dominik Oppmann

Possibilities and Limitations of the Structured Transposition of Normative Texts in Functions on Typed Data Structures

Abstract

Normative regulations, described in laws, decrees and judgments, are mainly represented in textual form. But this representation lacks of an easy comprehensibility and it also contains a lot of vague information that must be interpreted first. The whole task of norm interpretation is very complex, due to its time and labor intensity and the lack of proper tool support. Therefore, this master's thesis contributes to formalization for models based on legal texts by the usage of proper tool support.

The main goal in this work is the creation of a graphical model editor, which helps legal experts formalizing the decision-making structures in normative texts and represent the semantics of a text in a visual model. In the intended formalization process, the user can use several legal documents as base for creating a "semantic model" consisting of types with attributes and relations between each other. All model elements can be linked to the source text to justify their origin. The decisions are modeled in the attributes which can hold next to primitive data types also executable expressions (MxL).

The second part of this thesis consists of the creation of an environment to populate these semantic models with concrete data instances and evaluating the MxL expressions at runtime. Therefore, SocioCortex is used as a reasoning engine. The benefit of the evaluation environment is to enable the simulation for (hypothetical) cases even by unexperienced user that do not understand the intended semantics of normative texts in detail.