Connecting Digital Scholarly Researcher Identifiers & University Systems: Assessment of Engineering Faculty at a Major Research Institution. Over, S., Yin, M., Mazure, E. S., Stovall, C., Khan, M. S., Wang, J., Craig, B., & Miles, R. A. American Society for Engineering Education, June, 2026.
Connecting Digital Scholarly Researcher Identifiers & University Systems: Assessment of Engineering Faculty at a Major Research Institution [link]Paper  abstract   bibtex   
At Virginia Tech, a unit within University Libraries is responsible for supporting institution-wide efforts to improve impact and visibility of campus research. Beyond providing consultations and workshops for growing research impact, the unit evaluated and improved the research data ecosystem to ensure more complete and accurate data capture. Part of this process involved assessment of how researchers use, if at all, researcher scholarly identifiers (ID). Digital scholarly researcher identifiers, such as the ORCID iD and Scopus Author ID, are important for disambiguating researchers’ works and helping to capture accurate global impact data. This is especially critical for our institution’s College of Engineering, which contributes a large share of campus research outputs. The researcher IDs and systems involved in this project are Scopus Author IDs, ORCID iDs, Academic Analytics, Symplectic Elements profiles, and our institution’s Banner instance (human resources records). This paper will cover the process of finding, assessing, and integrating identifiers across systems for use in research impact reporting and benchmarking, including ways this can be applied to any research institution. The College of Engineering at Virginia Tech’s status of researcher IDs will be detailed along with related efforts by the University Libraries’ unit. Some surprising results included the number of duplicate IDs and incorrect institutions associated with IDs, leading to inaccurate reporting metrics. In the future, this work will be contained within an internal university data site for assessment by department heads and other leadership to improve Virginia Tech’s use of these key researcher IDs and their corresponding metrics.
@article{over_connecting_2026,
	title = {Connecting {Digital} {Scholarly} {Researcher} {Identifiers} \& {University} {Systems}: {Assessment} of {Engineering} {Faculty} at a {Major} {Research} {Institution}},
	shorttitle = {Connecting {Digital} {Scholarly} {Researcher} {Identifiers} \& {University} {Systems}},
	url = {https://hdl.handle.net/10919/143607},
	abstract = {At Virginia Tech, a unit within University Libraries is responsible for supporting institution-wide efforts to improve impact and visibility of campus research. Beyond providing consultations and workshops for growing research impact, the unit evaluated and improved the research data ecosystem to ensure more complete and accurate data capture. Part of this process involved assessment of how researchers use, if at all, researcher scholarly identifiers (ID). Digital scholarly researcher identifiers, such as the ORCID iD and Scopus Author ID, are important for disambiguating researchers’ works and helping to capture accurate global impact data. This is especially critical for our institution’s College of Engineering, which contributes a large share of campus research outputs. The researcher IDs and systems involved in this project are Scopus Author IDs, ORCID iDs, Academic Analytics, Symplectic Elements profiles, and our institution’s Banner instance (human resources records). This paper will cover the process of finding, assessing, and integrating identifiers across systems for use in research impact reporting and benchmarking, including ways this can be applied to any research institution. The College of Engineering at Virginia Tech’s status of researcher IDs will be detailed along with related efforts by the University Libraries’ unit. Some surprising results included the number of duplicate IDs and incorrect institutions associated with IDs, leading to inaccurate reporting metrics. In the future, this work will be contained within an internal university data site for assessment by department heads and other leadership to improve Virginia Tech’s use of these key researcher IDs and their corresponding metrics.},
	language = {en},
	urldate = {2026-07-13},
	publisher = {American Society for Engineering Education},
	author = {Over, Sarah and Yin, Mengyu and Mazure, Emily S. and Stovall, Connie and Khan, M. Shehryar and Wang, Jiren and Craig, Brian and Miles, Rachel A.},
	month = jun,
	year = {2026},
}

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