Big Law, Big Data

Abstract

It is often claimed in the media and in political and academic debates that more law nurtures more research, which in turn should generate more information. However, the question researchers are left with is the following: What does this mean for comparative law and its methods? This article takes the context of European consumer sales law as an example of the web of rules applicable at both the European and the national levels. In this context, the main idea behind this article is that looking at law and research as data to be built upon and used in further analysis can revolutionize the way in which legal research is understood. This is because current research methods in European consumer sales law fall short of systematically analysing the essential weaknesses of the current regulation system. In this contribution, I argue that the volume of regulation in European consumer law is large enough for it to be considered Big Data and analysed in a way that can harness its potential in this respect. I exemplify this claim with a case study consisting in the setting up of a Convergence Index that maps the converging effect of harmonizing policies adopted by the European legislator in the field of consumer sales law. This methodology builds on previous work by Siems on numerical comparative law, as well as on the Consumer Law Compendium database set up by Schulte-Nölke, and fills a gap in consumer literature while showcasing the importance of measurement indices. This contribution emphasizes the need to address the resulting complexity of European consumer sales law by further combining research methods and novel tools to uncover hidden patterns within and relationships between its different components.

Keywords: big data, numerical comparative law, empirical methods, Convergence Index, artificial intelligence, European consumer contract law, law and technology