Category: Visualization of Bibliographic Information from Library Databases

This project explores the best ways of visualizing 350 library databases to improve library instruction. “What do library resources include?” or “What does a library database include?” are two of the important questions to answer in a library instruction class. It is a persistent challenge to introduce library databases to students in an engaging, interesting, and meaningful way. Most library databases contain bibliographic information such as the names of authors, book and article titles, journal names, year of publication, reference citations, keywords, abstracts, full-text and so on. Any of these fields can be visualized to provide a better understanding of database content as Feng et al. (2015) assert in “Visualization and Quantitative Study in Bibliographic Databases” (Journal of Informetrics 9: 118-134).

This project falls into the category of direct, practical uses of computational methods for humanities research. It is methodological in focus, and uses statistically grounded, computer-enabled analysis that includes text mining, spatial analysis, and data visualization. The activities of this project are to:
1. Explore various open-source visualization tools such as Tableau Public, Power BI, and those listed on the SHU DH home page.
2. Provide visualization examples of selected library databases (see the postings below).
3. Offer collaborative workshops to librarians, teaching faculty, and students to invite feedback and to generate new ideas on the visualization of bibliographic information from library databases.
4. Create an appropriate blog to share the ideas beyond the funding of this project.
5. Recommend a new methodology for librarians to use in their instruction by August 31. 2016.
6. Attend monthly meetings to discuss progress/challenges/ideas among the DH faculty fellows and with members of the DH committee.
7. Present the project at a TLTR Best Practices Showcase in the academic year following the award.