Building visualization skills through investigating the journal of the medical library association coauthorship network from 2006–2017

Objective: The primary objective of this study was to explore different dimensions of Journal of the Medical Library Association (JMLA) authorship from 2006–2017. Dimensions that were evaluated using coauthorship networks and affiliation data included collaboration, geographical reach, and relationship between Medical Library Association (MLA) member and nonmember authors. A secondary objective was to analyze the practice and practical application of data science skills. Methods: A team of librarians who attended the 2017 Data Science and Visualization Institute used JMLA bibliographic metadata extracted from Scopus, together with select MLA membership data from 2006–2017. Data cleaning, anonymization, analysis, and visualization were done collaboratively by the team members to meet their learning objectives and to produce insights about the nature of collaborative authorship at JMLA. Results: Sixty-nine percent of the 1,351 JMLA authors from 2006–2017 were not MLA members. MLA members were more productive and collaborative, and tended to author articles together. The majority of the authoring institutions in JMLA are based in the United States. Global reach outside of the United States and Canada shows higher authorship in English-speaking countries (e.g., Australia, United Kingdom), as well as in Western Europe and Japan. Conclusions: MLA support of JMLA may benefit a wider network of health information specialists and medical professionals than is reflected in MLA membership. Conducting coauthorship network analyses can create opportunities for health sciences librarians to practice applying emerging data science and data visualization skills.