Creating Context Networks in Dutch Legislation

This paper describes ongoing research on automatically determining relevant context to display to a user of a legislative portal given the article they are retrieving, purely based on ‘objective’ criteria inferred from the network of sources of law. A first prototype is presented and a formative evaluation of it by legal expert users. Results are promising, but there is room for improvement

openlaws.eu: Overview on scientific publications

OpenLaws is an ambitious legal information project that builds on open data, open innovation and open source software. OpenLaws will help you find legal information more easily, organize it the way you want and share it with others. The Internet platform is adding a “social layer” to the existing “institutional layer” of legal information systems. Together with the different stakeholders, we will create a network between legislation, case law, legal literature and legal experts - both on a national and a European level, leading to better access to legal information. The openlaws core team will also create a “BOLD“ Vision 2020 about what Big Open Legal Data (BOLD) can do in the future and propose a roadmap to the European Commission. This report gives a short overview of all scientific publications produced during and immediately after the end of the project

Automatic Classification of Sentences in Dutch Laws

The work described here builds on [1], where we presented a categorisation of norms or provisions in legislation. We claimed that the categories are characterized by the use of typical sentence structures and that this would enable automatic detection and classification. In this paper we present the results of experiments in such automatic classification of provisions. We have defined fourteen different categories of provisions, and compiled a list of 81 sentence structures for those categories from twenty Dutch laws. Based on these structures, a parser was used to classify the sentences in fifteen different Dutch laws, classifying 94 % of 530 sentences correctly. It compares well with other, statistical approaches. An important improvement of our classifier will be the distinction of principal and auxiliary sentences

Kappen met asociaal gedrag

In 2006 and 2007 the municipality of Rotterdam conducted a pilot project under the name 'FF Kappe ('Cut it out'), aimed at curbing youth nuisance behaviour. FF Kappe is inspired by the Acceptable Behaviour Contracts (ABC) and Anti-Social Behaviour Orders (ASBO's) in England. The main question of the research is: what are the assumed active mechanisms of FF Kappe, in what context would they work and is it possible to identify side effects