Projects

Below are some examples of our (bigger) projects.

ASReview

ASReview is an innovative piece of software that was developed at Utrecht University’s DISC-AI lab to make systematic literature reviews more efficient using active learning. By quickly identifying relevant publications, ASReview helps researchers save valuable time while ensuring transparency in the review process.
 
As an open-source project, ASReview is widely applicable across scientific disciplines, contributing to reproducible and reliable research. It is continuously developed in collaboration with an international community of researchers, software developers, UX-designers, and users.
 
Want to learn more? Visit the ASReview website for the latest updates, tutorials, and opportunities to contribute.

MICE

mice (Multivariate Imputation by Chained Equations) is a powerful R package developed to handle missing data through multiple imputation, enabling researchers to perform robust and unbiased statistical analyses. By creating multiple plausible datasets that account for the incomplete data uncertainty, mice allows for valid inference even in the presence of incomplete data.
 
Widely used across disciplines such as epidemiology, social sciences, and official statistics, mice supports reproducible and transparent research analysis pipelines. As an open-source tool, it is actively maintained and developed by a group of missing data experts from our department with contributions by a vibrant community of statisticians, data scientists, and researchers worldwide.
 
Curious to explore more? Visit the mice webpage, the mice CRAN page or the GitHub repository for tutorials, documentation, and ways to get involved.

ODISSEI

ODISSEI (Open Data Infrastructure for Social Science and Economic Innovations) is the national research infrastructure for the Dutch social sciences. It unites about 45 member organisations (all Dutch social-science faculties, Statistics Netherlands, public research agencies, and other institutes) in a single, federated ecosystem. Through shared facilities such as CBS microdata access, the LISS Panel, high-performance computing and expert support, ODISSEI provides the data, tools and expertise needed for innovative, reproducible, and collaborative research. The scientific director of ODISSEI is Daniel Oberski.

ODISSEISoDa is ODISSEI’s in-house support team for data-intensive and computational social-science projects, offering free consultations and collaborations to researchers at ODISSEI member institutions. With expertise in data acquisition, large-scale analysis and research-software engineering, the team advances open, goal-oriented social-science projects through collaborations, workshops, tutorials and a fellowship programme. The SoDa team is based in the Methodology & Statistics section of Utrecht University and includes several researchers from our section.