Results - From Dogma to Data: Exploring How Case Law Evolves

The purpose of the project was to explore to which extent data science methods can be applied in the field of legal research in order to better and more comprehensively describe, analyse and understand the case law and its development in some field of international law. The project initially undertook to carry out this exploration in the field of 1) European Human Rights Law with a focus on the case law of the European Court  of Human Rights, 2) European Union Law with a focus on the case law of the Court of Justice of the European Union and 3) International Trade Law with a focus on the decisions issued by the Appellate branch of the World Trade Organisations Dispute Settlement Body. Subsequently the project narrowed its empirical scope to the first two courts. This was the result of a similar project being granted by the Swiss National Research Foundation to Professor Joost Pauwellyn to carry out a research project similar to Dogma to Data, but with an exclusive focus on WTO law. Dogma to Data has coordinated its research with the Geneva project via collaboration with Wolfgang Alschner who is now an assistant professor at the University of Ottawa.

Dogma to Data set out to test the applicability of mainly two kinds of data science methods: Automatic Summarization (which is a sub-discipline under Natural Language Processing) and Network Analysis. Early results in the project-period led to an abandonment of the Automatic Summarization leg of the project. While Automatic Summarization is working increasingly well for many kinds of tasks, the legal documents relevant to our project turned out to be too complex for even state-of-the- art programming to handle. The project has two peer reviewed publications which both contribute to the field, but since the project were pursuing research findings that could be translated into use for legal research purposes rather than just incremental advances in NLP, the PI decided to abandon this leg of the project.

Network Analysis on the other hand turned out to be a very fruitful research avenue. In a close collaboration between skilled data scientist and legal researchers the project has published a number of peer reviewed articles in both Danish and international journals that has truly contributed to advancing and indeed defining what is now referred to as computational legal studies.

Not only has the project shown how network analysis in areas of law that is characterised by very large amounts of case law is useful in identifying both the historical development of law, the relationship between various cases and in identifying various metrics for identifying the most important cases (from the court's point of view)

- the project has also contributed to the advancement of the data science components of network analysis. Using legal problems as a starting for developing methods that can be used to analyse the law has challenged data scientist working with the PI to develop ways of carrying more advanced forms of data analysis.

Finally the project has tested the practical use of its research in collaboration with a large Danish law firm. In two cases that has been decided by the Danish Supreme Court, has the projects research projects been applied to advance legal arguments that could not have been made in the same way without the research produced by the project. 

To conclude, the project has had high impact on legal research, both in Denmark and internationally, some impact in the field of applied network science and it has had societal impact through the use of its research in the context of legal practice. Overall, the projects research is likely to be picked up by future researchers and possibly also in the emerging business community of legal tech. The project will thereby have had a longstanding impact that is both scientific and societal