ORCID coverage in research institutions—Readiness for partially automated research reporting

Kathrin Schnieders 1
Sandra Mierz 2
Sabine Boccalini 3
Wibke Meyer Zu Westerhausen 3
Christian Hauschke 2
Stephanie Hagemann Wilholt 4
Sonja Schulze 1
1
 
Centralized Reporting, Osnabrueck University, Germany
2
 
Open Science Lab, Leibniz Information Centre for Science and Technology - TIB, Germany
3
 
University Library, Osnabrueck University, Germany
4
 
PID Competence Centre, Leibniz Information Centre for Science and Technology - TIB, Germany
Publication typeJournal Article
Publication date2022-11-10
scimago Q1
wos Q2
SJR0.576
CiteScore4.2
Impact factor1.6
ISSN25040537
General Medicine
Abstract

Reporting and presentation of research activities and outcome for research institutions in official, normative standards are more and more important and are the basis to comply with reporting duties. Institutional Current Research Information Systems (CRIS) serve as important databases or data sources for external and internal reporting, which should ideally be connected with interfaces to the operational systems for automated loading routines to extract relevant research information. This investigation evaluates whether (semi-) automated reporting using open, public research information collected via persistent identifiers (PIDs) for organizations (ROR), persons (ORCID), and research outputs (DOI) can reduce effort of reporting. For this purpose, internally maintained lists of persons to whom an ORCID record could be assigned (internal ORCID person lists) of two different German research institutions—Osnabrück University (UOS) and the non-university research institution TIB—Leibniz Information Center for Science and Technology Hannover—are used to investigate ORCID coverage in external open data sources like FREYA PID Graph (developed by DataCite), OpenAlex and ORCID itself. Additionally, for UOS a detailed analysis of discipline specific ORCID coverage is conducted. Substantial differences can be found for ORCID coverage between both institutions and for each institution regarding the various external data sources. A more detailed analysis of ORCID distribution by discipline for UOS reveals disparities by research area—internally and in external data sources. Recommendations for future actions can be derived from our results: Although the current level of coverage of researcher IDs which could automatically be mapped is still not sufficient to use persistent identifier-based extraction for standard (automated) reporting, it can already be a valuable input for institutional CRIS.

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Schnieders K. et al. ORCID coverage in research institutions—Readiness for partially automated research reporting // Frontiers in Research Metrics and Analytics. 2022. Vol. 7.
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Schnieders K., Mierz S., Boccalini S., Meyer Zu Westerhausen W., Hauschke C., Hagemann Wilholt S., Schulze S. ORCID coverage in research institutions—Readiness for partially automated research reporting // Frontiers in Research Metrics and Analytics. 2022. Vol. 7.
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TY - JOUR
DO - 10.3389/frma.2022.1010504
UR - https://doi.org/10.3389/frma.2022.1010504
TI - ORCID coverage in research institutions—Readiness for partially automated research reporting
T2 - Frontiers in Research Metrics and Analytics
AU - Schnieders, Kathrin
AU - Mierz, Sandra
AU - Boccalini, Sabine
AU - Meyer Zu Westerhausen, Wibke
AU - Hauschke, Christian
AU - Hagemann Wilholt, Stephanie
AU - Schulze, Sonja
PY - 2022
DA - 2022/11/10
PB - Frontiers Media S.A.
VL - 7
PMID - 36437858
SN - 2504-0537
ER -
BibTex
Cite this
BibTex (up to 50 authors) Copy
@article{2022_Schnieders,
author = {Kathrin Schnieders and Sandra Mierz and Sabine Boccalini and Wibke Meyer Zu Westerhausen and Christian Hauschke and Stephanie Hagemann Wilholt and Sonja Schulze},
title = {ORCID coverage in research institutions—Readiness for partially automated research reporting},
journal = {Frontiers in Research Metrics and Analytics},
year = {2022},
volume = {7},
publisher = {Frontiers Media S.A.},
month = {nov},
url = {https://doi.org/10.3389/frma.2022.1010504},
doi = {10.3389/frma.2022.1010504}
}