The Case for a Linked Data Research Engine for Legal Scholars

The Case for a Linked Data Research Engine for Legal Scholars

This contribution explores the application of data science and artificial intelligence to legal research, more specifically an element that has not received much attention: the research infrastructure required to make such analysis possible. In recent years, EU law has become increasingly digitised...

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Bibliographic Details
Published in:European journal of risk regulation 2020-03, Vol.11 (1), p.70-93
Main Authors: MOODLEY, Kody, HERNANDEZ-SERRANO, Pedro V, ZAVERI, Amrapali J, SCHAPER, Marcel GH, DUMONTIER, Michel, VAN DIJCK, Gijs
Format: Article
Language:eng
Subjects:
Artificial intelligence
Attributions
Case law
Competence
Deoxyribonucleic acid
DNA
Electronic publishing
Federal court decisions
Infrastructure
Judicial reviews
Legal information
Legal research
Methods
Permission
Reproduction
Researchers
Scholars
Science
Software
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Summary:This contribution explores the application of data science and artificial intelligence to legal research, more specifically an element that has not received much attention: the research infrastructure required to make such analysis possible. In recent years, EU law has become increasingly digitised and published in online databases such as EUR-Lex and HUDOC. However, the main barrier inhibiting legal scholars from analysing this information is lack of training in data analytics. Legal analytics software can mitigate this problem to an extent. However, current systems are dominated by the commercial sector. In addition, most systems focus on search of legal information but do not facilitate advanced visualisation and analytics. Finally, free to use systems that do provide such features are either too complex to use for general legal scholars, or are not rich enough in their analytics tools. In this paper, we motivate the case for building a software platform that addresses these limitations. Such software can provide a powerful platform for visualising and exploring connections and correlations in EU case law, helping to unravel the “DNA” behind EU legal systems. It will also serve to train researchers and students in schools and universities to analyse legal information using state-of-the-art methods in data science, without requiring technical proficiency in the underlying methods. We also suggest that the software should be powered by a data infrastructure and management paradigm following the seminal FAIR (Findable, Accessible, Interoperable and Reusable) principles .
ISSN:1867-299X
2190-8249