Abstract

The interpretation of normative texts, such as laws, or con- tracts, is a complex, knowledge-, time-, and mostly data-intensive task. Numerous attempts have already been made to formalize this process, which have met rather less approval in legal science and practice.

This paper describes a collaborative modeling environment to support the analysis and interpretation of statutory texts, i.e., laws. The paper performs a case study on formalizing the product liability act and pro- poses a data-centric process that enables the formalization of laws. The tool implements state-of-the-art text mining technologies to assist legal experts during the formalization of norms by automatically detecting key concepts within normative texts, e.g., legal definitions, prohibitions, obligations, etc. The work at hand elaborates on the implementation of data science environment and describes key requirements, a reference architecture and a collaborative user interface.