Application of an Ecosystem Methodology Based on Legal Language Processing for the Transformation of Court Decisions and Legal Opinions into Open Data

Abstract

Regulation of modern societies requires the generation of large sets of heterogeneous legal documents: bills, acts, decrees, administrative decisions, court decisions, legal opinions, circulars, etc. More and more legal publishing bodies publish these documents online, although usually in formats that are not machine-readable and without following Open Data principles. Until an open by default generation and publication process is employed, ex-post transformation of legal documents into Legal Open Data is required. Since manual transformation is a time-consuming and costly process, automated methods need to be applied. While some research efforts toward the automation of the transformation process exist, the alignment of such approaches with proposed Open Data methodologies in order to promote data exploitation is still an open issue. In this paper, we present a methodology aligned to the Open Data ecosystem approach for the automated transformation of Greek court decisions and legal opinions into Legal Open Data that builds on legal language processing methods and tools. We show that this approach produces Legal Open Data of satisfying quality while highly reducing the need for manual intervention.

Keywords

• akoma ntoso
• legal open data
• legal big data
• open data ecosystem
• natural language processing
• domain specific language
• legal parsing