Comparing different search methods for the open access journal recommendation tool B!SON

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 introduc...

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Bibliographic Details
Published in:International journal on digital libraries Vol. 25; no. 3; pp. 505 - 516
Main Authors: Entrup, Elias, Eppelin, Anita, Ewerth, Ralph, Hartwig, Josephine, Tullney, Marco, Wohlgemuth, Michael, Hoppe, Anett
Format: Journal Article
Language:English
Published: Berlin, Heidelberg Springer 01.09.2024
Springer Berlin Heidelberg
Springer Nature B.V
Subjects:
Academic libraries
Academic publishing
Academic work
Academic writing
Access
Application programming interface
Complex tasks
Computer Science
Copyright
Database Management
Feedback
Information Systems and Communication Service
Languages
Libraries
Open access
Open access publishing
Paper submission
Positive feedback
Recommendation system
Recommender systems
Requirements analysis
Scholarly journals
Sustainable development
Transparency
Paper submission
Scholarly journals
Academic publishing
Open access
Recommendation system
ISSN:1432-1300, 1432-5012, 1432-1300
Online Access:Get full text
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Summary: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.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:1432-1300
1432-5012
1432-1300
DOI:10.1007/s00799-023-00372-3