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recORD - Landscape analysis of open research data assessment practices within Swiss higher education institutions

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Datensatzübersicht

Datensatz-Titel

recORD - Landscape analysis of open research data assessment practices within Swiss higher education institutions

Kanonischer DOI

Ermöglicht das Zitieren des gesamten Datensatzes, unabhängig von Versionen.

https://doi.org/10.48573/s389-kw73

DOI

Ermöglicht das Zitieren einer spezifischen Datensatzversion.

https://doi.org/10.48573/gv7c-ck37

Sprache der Datensatzbeschreibung

Englisch

Datensatz URL

-

Verfügbarkeit der Daten

-

Datensatzbeschreibung

This dataset provides an overview of the current state of research assessment practices related to Open Research Data (ORD) within Swiss Higher Education Institutions (HEIs). The goal of this analysis is to delineate existing practices, requirements, and obstacles in assessing ORD across three levels: research proposals, individual researchers, and research units or institutions, depending on their administrative structures. The online survey was distributed to all Swiss universities, federal institutes of technology, universities of applied sciences, and universities of teacher education, according to the swissuniversities list from 2024. The survey focused on formalised research assessment practices and ORD policies and support.

Bemerkungen zur Dokumentation

The questionnaire "Survey on ORD Practices in Research Assessment" (file 32173) and the report "Assessing and Enabling Open Research Data Practices in Swiss Higher Education Institutions: A Comprehensive Landscape Analysis" (file 32176) provide an in-depth understanding of data collection and analysis.

Versionsnummer

1.0

Enddatum des Embargos

-

Publikationsdatum

07.11.2024

Hinweise zur Version

Version 1.0

Bibliografische Zitierung

Bornatici, C., Araujo, P., Heers, M., Ochsner, M., & Ramseyer, N. (2024). recORD - Landscape analysis of open research data assessment practices within Swiss higher education institutions (Version 1.0) [Data set]. FORS. https://doi.org/10.48573/gv7c-ck37

MD5-Hash des DIP

ce08f7789843dedd0759fcb78b2b8094

Inhalt des Datensatzes

/
metadata.yaml