Finding a suitable open access journal to publish scientific work is a complex task: Researchers have to navigate a constantly growing number of journals, institutional agreements with publishers, funders’ conditions and the risk of Predatory Publishers. To help with these challenges, we introduce a web-based journal recommendation system called B!SON. It is developed based on a systematic requirements analysis, built on open data, gives publisher-independent recommendations and works across domains. It suggests open access journals based on title, abstract and references provided by the user. The recommendation quality has been evaluated using a large test set of 10,000 articles. Development by two German scientific libraries ensures the longevity of the project.
Finding a suitable open access journal to publish academic work is a complex task: Researchers have to navigate a constantly growing number of journals, institutional agreements with publishers, funders’ conditions and the risk of predatory publishers. To help with these challenges, we introduce a web-based journal recommendation system called B!SON. A systematic requirements analysis was conducted in the form of a survey. The developed tool suggests open access journals based on title, abstract and references provided by the user. The recommendations are built on open data, publisher-independent and work across domains and languages. Transparency is provided by its open source nature, an open application programming interface (API) and by specifying which matches the shown recommendations are based on. The recommendation quality has been evaluated using two different evaluation techniques, including several new recommendation methods. We were able to improve the results from our previous paper with a pre-trained transformer model. The beta version of the tool received positive feedback from the community and in several test sessions. We developed a recommendation system for open access journals to help researchers find a suitable journal. The open tool has been extensively tested, and we found possible improvements for our current recommendation technique. Development by two German academic libraries ensures the longevity and sustainability of the system.
Im Anbau von Winterraps stehen wir nach Umstellung auf erucasäurefreie Sorten seit 1974 vor Einführung einer neuen Sortengeneration mit Doppelqualität, die sowohl erucasäurefrei als auch glucosinolatfrei ist. Alle Beteiligten – Züchter, Erzeuger und Verwertungsindustrie — sind sich einig, daß mit der höheren Qualität keine Einbuße an Quantität einhergehen darf. Seit Eintragung der ersten 00‐Sorte LIBRADOR und den nachfolgenden Eintragungen 1982 und 1983 liegen nunmehr auch Erfahrungen aus dem feldmäßigen Anbau von 00‐Sorten vor. Wenn auch die Ergebnisse noch nicht für das ganze Bundesgebiet Aussagekraft besitzen, so lassen die Erträge des Jahres 1983 und 1984 den Schluß zu, daß bei Einhalten der normalen Anbautechnik gleichwertige Erträge wie mit 0‐Sorten erreichbar sind.
Researchers’ task of finding a suitable open access journal for their work is becoming more and more complex: they have to comply with funder's conditions; their institutions hold various agreements with publishers; the number of journals is constantly growing (DOAJ 2018: 11.250 journals, 2021: >16.000 journals); so-called Predatory Publishers cause uncertainty. In order to reduce this complexity, TIB and SLUB Dresden, two major German research libraries, are developing B!SON, a web-based recommender for finding suitable Open Access journals. The tool calculates the similarity between a user's manuscript (title, abstract, references) and already published articles. Based on this similarity measure, B!SON will suggest Open Access journals in which similar articles have appeared. Researchers can use this information as guidance for their decision in which Open Access journal to publish. In addition, librarians can use B!SON for their publication support services and an API will allow the integration into existing library services. The results can be adapted to local conditions (e.g. price caps for institutional funding, Open Access agreements). The tool will use machine-learning techniques combined with a technical implementation of bibliometric algorithms proven in library practice. For this purpose, we will rely on the DOAJ article-level metadata corpus and the OpenCitations Index. We will analyze which article components give most reliable results in textual similarity analysis. Due to the ever-changing corpus of underlying data, the training process will be repeated regularly in the final tool. The information about journals (keywords, license, fees, etc.) will be provided by the DOAJ as well. We have built a community of researchers and librarians that we regularly consult in terms of specifications for the tool as well as – later in the project – acceptance and quality of its results. We plan to provide a beta version of B!SON in spring 2022. The project is funded by the German Federal Ministry of Education and Research. We present our schedule, facts and figures of the B!SON project and focus particularly on technical concepts of the project.
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