Jot: guiding journal selection with suitability metrics




journal selection, web application, bibliometrics, visualization, scientific publishing, open access publishing, open source software, data integration


Researchers grapple with a challenging and consequential decision each time they choose a journal for manuscript submission. There are several online tools that attempt to identify appropriate journals for a manuscript, but each of these tools has shortcomings in terms of the journal data they provide and the exploration functionality they offer—and not one of these tools is open source. Jot is a free and open-source web application that matches manuscripts in the fields of biomedicine and life sciences with suitable journals, based on a manuscript's title, abstract and (optionally) citations. Jot gathers a wealth of data on journal quality, impact, fit, and open access options that can be explored through a dashboard of linked, interactive visualizations. Visit Jot at, or run your own Jot server using our open-source Python package 'journal_targeter', available from the Python Package Index (PyPI).

Author Biography

Jeffrey P. Townsend, Department of Biostatistics, Yale School of Public Health, New Haven, CT

Elihu Professor of Biostatistics and Professor of Ecology and Evolutionary Biology; Co-Leader, Genomics, Genetics, & Epigenetics Research Program


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