Optimizing ASReview simulations with multiprocessing solutions for ‘light-data’ and ‘heavy-data’ users via a Kubernetes cluster.
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.