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This paper describes the Eunomos software, an advanced legal document and knowledge management system, based on legislative XML and ontologies. We describe the challenges of legal research in an increasingly complex, multi-level and multi-lingual world and how the Eunomos software helps users cut through the information overload to get the legal information they need in an organized and structured way and keep track of the state of the relevant law on any given topic. We describe the core system from workflow and technical perspectives, and discuss applications of the system for various user groups and our long term vision towards an Internet of Social Things, where laws can have an identity and be manipulated adding interpretation and can proactively inform interested users of their changes over time.

Abstract. The Radial Coordinate Visualization (Radviz) technique has been widely used to effectively evaluate the existence of patterns in highly dimensional data sets. A crucial aspect of this technique lies in the arrangement of the dimensions, which determines the quality of the posterior visualization. Dimension arrangement (DA) has been shown to be an NP-problem and different heuristics have been proposed to solve it using optimization techniques. However, very little work has focused on understanding the relation between the arrangement of the dimensions and the quality of the visualization. In this paper we first present two variations of the DA problem: (1) a Radviz independent approach and (2) a Radviz dependent approach. We then describe the use of the Davies-Bouldin index to automatically evaluate the quality of a visualization i.e., its visual usefulness. Our empirical evaluation is extensive and uses both real and synthetic data sets in order to evaluate our proposed methods and to fully understand the impact that parameters such as number of samples, dimensions, or cluster separability have in the relation between the optimization algorithm and the visualization tool.

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The automated identification of national implementations (NIMs) of European directives by text similarity techniques has shown promising preliminary results. Previous works have proposed and utilized unsupervised lexical and semantic similarity techniques based on vector space models, latent semantic analysis and topic models. However, these techniques were evaluated on a small multilingual corpus of directives and NIMs. In this paper, we utilize word and paragraph embedding models learned by shallow neural networks from a multilingual legal corpus of European directives and national legislation (from Ireland, Luxembourg and Italy) to develop unsupervised semantic similarity systems to identify transpositions. We evaluate these models and compare their results with the previous unsupervised methods on a multilingual test corpus of 43 Directives and their corresponding NIMs. We also develop supervised machine learning models to identify transpositions and compare their performance with different feature sets.

This paper describes a new concept of legal ontology together with an ontology development tool, called European Legal Taxonomy Syllabus (ELTS). The tool is used to model the legal terminology created by the Uniform Terminology project on EU consumer protection law as an ontology.ELTS is not a formal ontology in the standard sense, i.e., an axiomatic ontology formalized, for instance, in description logic. Rather, it is a lightweight ontology, i.e. a knowledge base storing low-level legal concepts, connected via low-level semantic relations, and related to linguistic patterns that denote legal concepts in several languages spoken in the European Union (EU). In other words, ELTS is a multi-lingual and multi-jurisdictional terminological vocabulary enriched with concepts denoted by vocabulary entries, with semantic relations between different concepts. The choice of such an architecture is based on past studies in comparative law and is motivated by the need to reveal the differences between national systems within the EU. Past literature in comparative law highlights that axiomatic ontologies freeze legal knowledge in an unreal steadiness, i.e., they render it disconnected from legal practice. Much more flexibility is needed to make the knowledge base acceptable to legal practitioners.ELTS was developed together with legal practitioners on the basis of the comparative view of European law. The ontology framework is designed to help professionals study the meaning of national and European legal terms and how they inter-relate in the transposition of European Directives into national laws. The structure and user interface of ELTS is suitable for building multi-lingual, multi-jurisdictional legal ontologies in a bottom-up and collaborative manner, starting from the description of legal terms by legal experts. It also takes into account the interpretation of norms, the dynamic character of norms and the contextual character of legal concepts in that they are linked to their legal sources (legislation, case law and doctrine).