(Aug 2026) B!SON is a tool that recommends open access journals based on a particular manuscript, while providing full transparency on what its recommendations are based on. By supporting and simplifying the journal selection process, B!SON supports authors in all career stages who are looking for the best-fitting open access journal. In addition, it can help academic libraries provide guidance to their researchers with identifying the best place to share their research results, even offering an option to use an institutionally adapted B!SON version. B!SON’s algorithm is based on machine learning and uses open data sources, including article and journal metadata from DOAJ. B!SON, just like DOAJ, can therefore be seen as a building block of the open scholarly infrastructure ecosystem.
B!SON is very simple to use: key parts of the manuscript—title, abstract, and references—are entered into the input form. B!SON processes the input and returns a list of fitting open access journals, ordered by a score indicating whether the journal has published articles that address the same or similar research topics as the input manuscript.
Behind the scenes, B!SON’s algorithm analyses article metadata and citation patterns to generate journal recommendations semantically and bibliometrically. More precisely, semantic and bibliometric similarities between the manuscript information entered and articles that have appeared in DOAJ-listed journals are evaluated.
Find out more here.
