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Board 96 : Leveraging Python to Improve Quality of Metadata of Engineering Faculty Publication Records

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Conference

2018 ASEE Annual Conference & Exposition

Location

Salt Lake City, Utah

Publication Date

June 23, 2018

Start Date

June 23, 2018

End Date

July 27, 2018

Conference Session

Engineering Libraries Division Poster Session

Tagged Division

Engineering Libraries

Page Count

8

Permanent URL

https://peer.asee.org/30145

Download Count

34

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Paper Authors

biography

Qianjin Zhang University of Iowa Orcid 16x16 orcid.org/https://0000-0003-0738-9357

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Qianjin (Marina) Zhang is Engineering & Informatics Librarian at the Lichtenberger Engineering Library. As a subject librarian, her work focuses on instruction, reference, consultation services and collection management for the engineering faculty and students. She’s also interested in research data management and support Research Data Services. She holds a MA in Information Resources & Library Science from The University of Arizona (Tucson, AZ), and a BS in Biotechnology from Jiangsu University of Science and Technology (Zhenjiang, China).

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Abstract

The Engineering Library at the University of Iowa conducted a project which consisted of reviewing metadata of engineering faculty publications in the Academic and Professional Records (APR), which is a locally branded faculty profile system. The challenge of the project was that there are thousands of records with erroneous or missing metadata, making it difficult to manually check Digital Object Identifier (DOI) and ISSN. Our strategy was to analyze the complete dataset, break it down into subsets with some common patterns and then focus on those subsets. The processes were conducted using Python. As a result, we prioritized records that have almost complete metadata but missing DOI and/or ISSN, retrieved DOI from PubMed and CrossRef online queries separately and added ISSN by matching journal titles or conference names with authorities. The implementation of Python can not only make the review process effective and efficient but also expand library services to the APR project.

Zhang, Q. (2018, June), Board 96 : Leveraging Python to Improve Quality of Metadata of Engineering Faculty Publication Records Paper presented at 2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah. https://peer.asee.org/30145

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