Caselawnet constructs citation networks from collections of Dutch case law.


Cite this software

What caselawnet can do for you

  • Search tool for legal experts or students, interested in in network analysis
  • Search publicly available Dutch judgments on keywords and download the result as a network
  • The exported network can be visualized in the Case Law App
  • Provides both a graphical user interface and a python package

The law is a text that describes what a person or legal entity can and cannot do. However, the law is somewhat open to interpretation. This interpretation is done by judges whenever a case is brought to court. Over time, the outcome of individual cases build what is called case law.

Because consistency is crucial for the fair application of the law, cases often reference other cases: if the reasoning behind a ruling in one case also applies to another case, then the ruling should be the same. To warrant consistency it is thus paramount that any relevant rulings from previous cases are identified. Conventionally, both the justice department and the defense depend on legal experts to make this identification when preparing a case. However, court rulings are often difficult to understand, there is only limited time available, and even experts are not aware of all cases that may be relevant.

To help mitigate this situation, the Netherlands eScience Center worked together with Maastricht University to develop an interactive visualization that assists the legal community at large (prosecutors, judges, lawyers, legal aids, but also researchers and students) in analyzing case law.

To analyze a specific topic or theme in the law, a collection of law cases first need to be represented as a network or graph. Each node in the graph represents a case, while the edges represent references to other cases. The caselawnet tool is basically a search machine, that retrieves the cases related to a search term, as well as the citations between those cases. The network can be downloaded and directly used in the visualization.

Programming languages
  • Jupyter Notebook 92%
  • Python 7%
  • HTML 1%
</>Source code

Participating organisations

Social Sciences & Humanities
Social Sciences & Humanities
Maastricht University
Netherlands eScience Center


Contact person

Dafne van Kuppevelt

Dafne van Kuppevelt

Netherlands eScience Center
Mail Dafne
Dafne van Kuppevelt
Dafne van Kuppevelt
Netherlands eScience Center

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