Titel:	ORCID coverage in research institutions - Readiness for partially automated research reporting
Autor(en):	Schnieders, Kathrin Mierz, Sandra Boccalini, Sabine Meyer zu Westerhausen, Wibke Hauschke, Christian Hagemann-Wilholt, Stephanie Schulze, Sonja
ORCID des Autors:	https://orcid.org/0000-0003-2499-7741 https://orcid.org/0000-0002-3666-0815 https://orcid.org/0000-0002-1149-9623 https://orcid.org/0000-0002-2448-413X
Zusammenfassung:	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.
Bibliografische Angaben:	Schnieders K, Mierz S, Boccalini S, Meyer zu Westerhausen W, Hauschke C, Hagemann-Wilholt S and Schulze S (2022): ORCID coverage in research institutions—Readiness for partially automated research reporting. Front. Res. Metr. Anal. 7:1010504.
URL:	https://doi.org/10.48693/301 https://osnadocs.ub.uni-osnabrueck.de/handle/ds-202305028761
Schlagworte:	(semi-)automated research reporting; linked open metadata; current research information system (CRIS); persistent identifier (PID); ORCID; ROR; FREYA; OpenAlex
Erscheinungsdatum:	10-Nov-2022
Lizenzbezeichnung:	Attribution 4.0 International
URL der Lizenz:	http://creativecommons.org/licenses/by/4.0/
Publikationstyp:	Einzelbeitrag in einer wissenschaftlichen Zeitschrift [Article]
Enthalten in den Sammlungen:	Open-Access-Publikationsfonds Publikationen der UB UOS Hochschulschriften

Diese Ressource wurde unter folgender Copyright-Bestimmung veröffentlicht: Lizenz von Creative Commons