Research

Explore the future of active learning in systematic reviewing

Explore the future of active learning in systematic reviewing

The ASReview Research Team consistently explores and investigates new ways to improve ASReview through simulation studies, use cases, and more. These endeavors often involve collaborations with various organizations, research groups, and developers. The outcomes of these investigations are published in peer-reviewed journals like Nature Machine Intelligence, ensuring transparency and credibility through the publication of data, scripts, and underlying code.

The ASReview project was initiated in 2018 when Prof. dr Rens van de Schoot, dr. Daniel Oberski and Prof. dr. Lars Tummers launched it at Utrecht University. The award-winning project has since evolved into a comprehensive multidisciplinary research team that closely intertwines with the ASReview community.

Research Principles

Research Principles

The team works according to the Open Science principles and invests in an inclusive community contributing to the project. In short, research is conducted according to the following fundamental principles:

  1. Research output should be FAIR (Finable Accessible Interoperable and Reusable).
  2. Research should be conducted with integrity, and we commit ourselves to the Netherlands Code of Conduct for Research Integrity.
  3. Output should be rewarded according to the Declaration on Research Assessment (DORA)

Utrecht University has established specific regulations governing conduct for its employees. These are based on the key principles of professional and quality academic conduct and ethically-responsible research. Members of the team employed by Utrecht University, commit themselves to these regulations in all their conduct, including all work related to ASReview. Adherence to similar key principles is expected of all researchers involved in all facets of the ASReview project.

Open science at Utrecht University
FAIR data principles
Declaration on Research Assessment Declaration

Research Projects and Output

Research Projects and Output

The FORAS project

The FORAS project will replicate and extend an original review integrating advanced machine-learning techniques via the OpenAlex database.

View Project

Research Partners

Research Partners

Research partner ASReview: Utrecht University
Research partner ASReview: NWO
Research partner OCRE ASReview
Research partner ASReview: EFSA
Research partner ASReview: KNMP
Research partner ASReview: KI-FMS
Research partner ASReview: DJI
Research partner ASReview: Centre for Urban Mental Health
Research partner ASReview: UvA
Research partner ASReview: AI department from Radboud University
Research partner ASReview: Nationaal Politielab AI - Utrecht
Research partner ASReview: Kinderformularium
Research partner ASReview: Open Evidence