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Building visualization skills through investigating the Journal of the Medical Library Association coauthorship network from 2006–2017
Journal of the Medical Library Association ( IF 2.9 ) Pub Date : 2020-04-01 , DOI: 10.5195/jmla.2020.775
Rebecca Reznik-Zellen 1 , Alexander J Carroll 2 , Eileen G Harrington 3 , Douglas James Joubert 4 , Tyler Nix 5 , Kristine M Alpi 6
Affiliation  

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.

中文翻译:

通过调查 2006-2017 年医学图书馆协会杂志合着网络建立可视化技能

目的 本研究的主要目的是探索 2006-2017 年医学图书馆协会杂志 (JMLA) 署名的不同维度。使用共同作者网络和隶属关系数据评估的维度包括协作、地理范围以及医学图书馆协会 (MLA) 成员和非成员作者之间的关系。次要目标是分析数据科学技能的实践和实际应用。方法 参加 2017 年数据科学与可视化研究所的一组图书馆员使用从 Scopus 中提取的 JMLA 书目元数据,以及 2006-2017 年精选的 MLA 成员数据。数据清洗、匿名化、分析、和可视化是由团队成员协作完成的,以满足他们的学习目标,并产生关于 JMLA 协作作者性质的见解。结果 2006-2017 年的 1,351 名 JMLA 作者中有 69% 不是 MLA 成员。MLA 成员更有生产力和协作性,并且倾向于一起撰写文章。JMLA 中的大多数创作机构都位于美国。在美国和加拿大以外的全球范围内,英语国家(例如澳大利亚、英国)以及西欧和日本的作者数量较高。结论 MLA 对 JMLA 的支持可能会比 MLA 成员所反映的更广泛的健康信息专家和医疗专业人员网络受益。
更新日期:2020-04-01
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