Presentation Type

Lightning Talk

Location

Zoom. Recording Coming Soon!

Start Date

16-4-2024 1:20 PM

End Date

16-4-2024 1:40 PM

Description

There is a growing interest in the use of publicly available metadata to convey scholarly impact as well as inform the provisioning of research services. In this study, we used metadata derived from API queries to three online community databases – DataCite, Crossref, and Unpaywall – to analyze datasets shared by researchers affiliated with Oklahoma State University (OSU). Initially, the dataset comprised of a collection of metadata pulled from DataCite, which included information such as dataset title, DOI, authors, publisher, publication year, and relation to other scholarly works. We streamlined the dataset to highlight OSU-affiliated authors and datasets only, corrected author name formats, and removed duplicates and erroneous entries. We matched OSU author information with data extracted from our university faculty profile system to assign departmental and college affiliations as well as ORCID iDs to each individual, where possible. We extracted, collated, and cleaned meaningful information from a corpus of academic articles that cited these datasets, obtaining article metadata from Crossref and subsequent open access metadata from Unpaywall. Our analysis explored citation patterns, publication trends, faculty/departmental representations, and co-authorship networks among OSU authors. Citation histograms, co-authorship networks, and publication timelines will be utilized to provide an improved understanding of data sharing at OSU. Insights from the visualizations will reveal trends in citation frequency, collaborative networks among researchers, and publication dynamics over time. The results of this research will contribute to the understanding of scholarly communication dynamics within the OSU academic community, improve the quality of services offered by research support personnel, and offer a basis for future research exploring data sharing practices within specific academic institutions.

Author Bios

Rhoda Alawiye is a graduate research assistant within the Research and Learning Services Department at the Oklahoma State University Libraries. With a solid background in Statistics, she is pursuing her master’s degree in Business Analytics and Data Science, set to be completed this spring. She epitomizes a passion for harnessing the power of data to drive insightful decision-making.

Dani Kirsch is a Research Data Specialist at the Oklahoma State University Libraries and will be defending her Ph.D. in Integrative Biology this semester. Much of her work involves providing research and data support to faculty, staff, and students through individual consultations, workshops, and review of data management and sharing plans and practices.

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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Apr 16th, 1:20 PM Apr 16th, 1:40 PM

Using Publicly Available Metadata to Analyze Data Sharing Practices at Oklahoma State University

Zoom. Recording Coming Soon!

There is a growing interest in the use of publicly available metadata to convey scholarly impact as well as inform the provisioning of research services. In this study, we used metadata derived from API queries to three online community databases – DataCite, Crossref, and Unpaywall – to analyze datasets shared by researchers affiliated with Oklahoma State University (OSU). Initially, the dataset comprised of a collection of metadata pulled from DataCite, which included information such as dataset title, DOI, authors, publisher, publication year, and relation to other scholarly works. We streamlined the dataset to highlight OSU-affiliated authors and datasets only, corrected author name formats, and removed duplicates and erroneous entries. We matched OSU author information with data extracted from our university faculty profile system to assign departmental and college affiliations as well as ORCID iDs to each individual, where possible. We extracted, collated, and cleaned meaningful information from a corpus of academic articles that cited these datasets, obtaining article metadata from Crossref and subsequent open access metadata from Unpaywall. Our analysis explored citation patterns, publication trends, faculty/departmental representations, and co-authorship networks among OSU authors. Citation histograms, co-authorship networks, and publication timelines will be utilized to provide an improved understanding of data sharing at OSU. Insights from the visualizations will reveal trends in citation frequency, collaborative networks among researchers, and publication dynamics over time. The results of this research will contribute to the understanding of scholarly communication dynamics within the OSU academic community, improve the quality of services offered by research support personnel, and offer a basis for future research exploring data sharing practices within specific academic institutions.