Towards OER Statistics: Data Requirements for the Scientometric Analysis of Open Educational Resources

The responsible research assessments initiative aims to broaden the scope of what can be recognised in science evaluation. As a scientometric approach, the open educational resources (OER) statistics framework contributes to this mission by rewarding academic teaching as a performance class via OER....

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Main Author: Kullmann Sylvia
Format: Article
Language:English
Published: De Gruyter 2025-06-01
Series:Open Information Science
Subjects:
Online Access:https://doi.org/10.1515/opis-2025-0017
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author Kullmann Sylvia
author_facet Kullmann Sylvia
author_sort Kullmann Sylvia
collection DOAJ
description The responsible research assessments initiative aims to broaden the scope of what can be recognised in science evaluation. As a scientometric approach, the open educational resources (OER) statistics framework contributes to this mission by rewarding academic teaching as a performance class via OER. Specialised OER infrastructures can be considered data providers for OER statistics. The analysis of selected OER infrastructures shows that in order to obtain comprehensive OER-related datasets that can be used for the determination of the OER statistics without significant additional effort, improvements in the metadata provided are needed. This applies to the completeness of databases, the use of persistent identifiers, and the references and attributions/citations of OER, but also to details such as information on quality, year of creation, version management, or granularity of OER.
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spelling doaj-art-78ec1b0db7b14bf891f55ff43a67b4832025-08-20T03:27:35ZengDe GruyterOpen Information Science2451-17812025-06-0191243210.1515/opis-2025-0017Towards OER Statistics: Data Requirements for the Scientometric Analysis of Open Educational ResourcesKullmann Sylvia0Information Center for Education, DIPF Leibniz Institute for Research and Information in Education, Rostocker Straße 6, 60323, Frankfurt am Main, GermanyThe responsible research assessments initiative aims to broaden the scope of what can be recognised in science evaluation. As a scientometric approach, the open educational resources (OER) statistics framework contributes to this mission by rewarding academic teaching as a performance class via OER. Specialised OER infrastructures can be considered data providers for OER statistics. The analysis of selected OER infrastructures shows that in order to obtain comprehensive OER-related datasets that can be used for the determination of the OER statistics without significant additional effort, improvements in the metadata provided are needed. This applies to the completeness of databases, the use of persistent identifiers, and the references and attributions/citations of OER, but also to details such as information on quality, year of creation, version management, or granularity of OER.https://doi.org/10.1515/opis-2025-0017open educational resourcesscientometric analysisresponsible research assessmentoer statisticsrecognition and reward system
spellingShingle Kullmann Sylvia
Towards OER Statistics: Data Requirements for the Scientometric Analysis of Open Educational Resources
Open Information Science
open educational resources
scientometric analysis
responsible research assessment
oer statistics
recognition and reward system
title Towards OER Statistics: Data Requirements for the Scientometric Analysis of Open Educational Resources
title_full Towards OER Statistics: Data Requirements for the Scientometric Analysis of Open Educational Resources
title_fullStr Towards OER Statistics: Data Requirements for the Scientometric Analysis of Open Educational Resources
title_full_unstemmed Towards OER Statistics: Data Requirements for the Scientometric Analysis of Open Educational Resources
title_short Towards OER Statistics: Data Requirements for the Scientometric Analysis of Open Educational Resources
title_sort towards oer statistics data requirements for the scientometric analysis of open educational resources
topic open educational resources
scientometric analysis
responsible research assessment
oer statistics
recognition and reward system
url https://doi.org/10.1515/opis-2025-0017
work_keys_str_mv AT kullmannsylvia towardsoerstatisticsdatarequirementsforthescientometricanalysisofopeneducationalresources