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    Data Visualization: A New Way to See Historical Records in the AFL-CIO Archive
    (2024-06-06) Eidson, Jennifer Gathings; Fettig, Rosemarie
    In the outreach phase of the Advancing Workers’ Rights grant, a three-year project that digitized over 90,000 pages of records from the AFL-CIO Civil Rights Department, creating social media and blog posts about the newly-available materials resulted in a quest for different ways to represent the materials in a unique, interesting, and user-friendly way. This search led us to explore data visualizations, for which a broad spectrum of graphical representations of information and data is possible. Two archivists discuss how a collaboration between student assistants and SCUA staff resulted in the creation of a series of data visualizations - maps, word clouds, and timeline graphs - that transformed the metadata from the digitized materials into unique and useful graphics. The graphics provide a new point of entry into the collection by using freely available tools like DataWrapper and Voyant, and the existing capabilities of Excel. The dataset originally exported from ArchivesSpace for use in Archelon was used for this outreach project and provides an example of how existing datasets can be reused to analyze collection materials in new ways. After applying these methods and tools to the materials selected for digitization, about 30% of the AFL-CIO Civil Rights Department records, we will share additional visualizations that comprise the complete records of the collection for further comparison and analysis of this approach.
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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, 2020) Reznik-Zellen, Rebecca; Carroll, Alexander J.; Harrington, Eileen G.; Joubert, Douglas James; Nix, Tyler; Alpi, Kristine M.
    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.
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    RDA and Linked Data: A New Way to Look at the Henson Collection
    (2016-06-08) Glennan, Kathy
    In 2005, the University of Maryland acquired over 70 digital videos spanning 35 years of Jim Henson’s groundbreaking work in television and film. To support in-house discovery and use, the collection was cataloged in detail using AACR2 and MARC21, and a web-based finding aid was also created. In the past year, I created an "r-ball" (a linked data set described using RDA) of these same resources. The presentation will compare and contrast these three ways of accessing the Jim Henson Works collection, with insights gleaned from providing resource discovery using RIMMF (RDA in Many Metadata Formats).