Universiteit Leiden

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Data Science Research Programme


The Faculty of Law

Leiden Law School is one of the largest faculties at Leiden University. With its international focus and roots going far back in the Dutch legal order, the faculty has helped to train many generations of legal professionals for key positions within a society governed by the rule of law. The research of the faculty is not restricted to just one core issue, but aims at excellent cutting-edge research across the full breadth of law. 

Data Science Research Projects

Measuring relevance and relations of Dutch legal publications

Gineke Wiggers

Legal scholars and professionals are confronted with a rapidly increasing volume of legal publications. Only part of these publications are relevant enough to be cited. This project aims to determine which documents that are, and whether alternative metrics are a reliable way to predict whether documents will be cited, in order to be able to present the user the most relevant publications first. 

The international tax system as a complex system

Manon Wintgens

The international tax system is composed of multiple layers, i.e., law and regulations,  jurisdictions, and businesses. Previously, these inherently different layers were often analysed from a fiscal perspective. In contrast, this data-driven research project aims to study the international tax system in its entirety from a complex systems perspective.

Complex systems can be characterized as systems in which multiple components interact with each other, often in non-linear ways. The main goal of this research will be to investigate if and how the international tax system can be defined and modelled as a complex system. Approaching the international tax system from this perspective aims to gain new insights on all layers, e.g., 1) on the effect of new and modified tax treaties; 2) on the interaction between jurisdictions; and 3) on the behaviour of business strategies over time. In addition, the project will address questions related to the existence of, e.g., tax gaps, legislative patterns, and tax havens and how these are reflected in observational data.

The project takes an innovative approach that combines data science with system modelling on data sources including tax treaties and financial information of businesses. By applying, e.g., network modelling and pattern discovery, the researchers aim to understand the behaviour of the international tax system as a complex system.

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