Data Science and Law
Data Science is a rapidly evolving field of research. This webpage aims to be a portal to ‘Data Science and Law’ activities and a platform for a broader community of researchers, teachers and other users who take an interest in the field. It is run by the Steering Group Data Science and Law of Tilburg Law School.
DSC/t teaches data science to students, upcoming researchers and business professionals. For this purpose various educational programs have been developed:
- Master Data Science and Society
- Master Business Analytics and Operations Research
- Master Marketing Analytics
In addition, the Provincial Government of Noord-Brabant, the Municipality of ‘s-Hertogenbosch, Tilburg University, and Eindhoven University of Technology have invested in the development of new study programs:
- joint Bachelor Data Science at TU/e and Tilburg University;
- joint Master Data Science and Entrepreneurship;
- special master’s program Data Science in Engineering at TU/e.
Data science is a multidisciplinary scientific field, with a large role for computer science and mathematical and statistical techniques, as well as human-technology interaction, social sciences and legal and ethical aspects. Data Science Center Tilburg is unique in that it combines these areas of expertise from Tilburg University’s different Schools.
Tilburg University’s research is based on a strong tradition of quantitative and technical research skills. In DSC/t its extensive knowledge in applied data science is combined with strong expertise in communication as well as values, ethics and regulatory and legal implications.
What is ‘Data Science and Law’?
We understand the term ‘Data Science and Law’ to contain all research focused on the relationship between law and data. ‘Data’ in this context is defined broadly to include files made up of bits and bytes, suited for statistical use, but also other digital applications or set of data with context that make the data transform in information, and of course ‘big data’ (i.e. data of a very large size, complex and unstructured data). Data are entering our society in many levels, the data-driving society or the ‘datafication’ of humans, organisations and our belongings (Internet of Things) will make it possible to research and discover patterns and relations we never could before. Or as Data Scientists say:
‘The ultimate goal of Data Science is not to collect more data, but to turn volume into real-world value. In fact, visualization of data can help discover patterns that were never noticed before and provide answers to questions that have never before been asked.’
For researchers, at least three perspectives on data science and law present themselves.
- Data subject to regulation.
In this perspective the focus is on how law and governance structures can, do or should respond to the emergence of data-related innovation. Examples of questions examined under this heading are: which rules apply to the ownership, licensing and transfer of big data? Who is liable for damage caused by self-driving cars? How can privacy and data protection be guaranteed for users of digital media? Are the police allowed to collect and combine data from various sources, including from secret surveillance, social media and data gathered by private companies, to investigate potential criminal offences?
- Law informed by data science.
One question central in this perspective is how the aforementioned data sources can be used to develop or evaluate law and regulation. Can empirical studies help answer what regulation should look like? Which methods produce useful and reliable results for fact based legislation? And how is data ‘translated’ into normative standpoints on the form and substance of regulation?
- Application of data in legal procedures and analytics.
This field considers the use of data in legal procedures and in the legal profession, focusing for example on the increased use of digital media in court proceedings and the effects this has on litigants. Questions falling under this heading are: how can data science inform judges’ decisions, and how can legal analytics can be used to, in part, take over the role of lawyers? Also, possibilities are being created through the sharing of data to create websites where users can calculate their chances of success in court (e.g. in an unfair dismissal procedure).
What does the Steering Group do?
The Steering Group Data Science and Law has three main aims. First, it seeks to bring together researchers from the Law School who share an interest in data science to combine their research efforts into new projects and activities. The steering group provides a forum in which to discuss and encourage new research. Through the input from researchers of various disciplinary backgrounds (e.g. public law, legal ethics, governance, private law, business law, criminal law, victimology and psychology), researchers are challenged to think beyond the boundaries of their own fields and to explore ‘data science and law’ in a broad societal context. Big data, for example, has implications for criminal law, (corporate) governance, privacy, private law and numerous other areas. Second, the steering group discusses the coordination of education on law and data science between TLS, the Data Science Center Tilburg (DSC/t), the Data Science Center Eindhoven (DSC/e) and the Jheronimus Academy of Data Science (JADS). Third, the Steering Group advises the Faculty Board of TLS on faculty matters relating to data science and law.
The members of the Steering Group Law and Data Science are:
- Marlies van Eck (PER)
- Koen van Holten (TIRO)
- Dr. Wesley Kaufmann (TSPB)
- Dr. Leontien van der Knaap (Intervict)
- Anne Lafarre (Business Law)
- Prof. Pierre Larouche (TILEC)
- Prof. Vanessa Mak (Private Law)
- Dr. Marloes van Noorloos (Criminal Law)
- Dr. Linnet Taylor (TILT)
- Prof. Eric Tjong Tjin Tai (Private Law)
- Prof. Peter van der Velden (Intervict)
- Jurgen van der Roest (student-assistant and secretary of the Steering Group)
- Jheronimus Academy of Data Science
- Big Data research Tilburg