13. Verwendete Literatur

Altenhöner, Reinhard / Berger, Andreas / Bracht, Christian / Klimpel, Paul / Meyer, Sebastian / Neuburger, Andreas / Stäcker, Thomas / Stein, Regine: DFG-Praxisregeln „Digitalisierung“, aktualisierte Fassung 2022 (dt.), https://doi.org/10.5281/zenodo.7435724 und dies.: DFG Practical Guidelines on Digitisation, Updated version 2022 (engl.), https://doi.org/10.5281/zenodo.7561148

Cremer, Fabian / Klaffki, Lisa / Steyer, Timo: Der Chimäre auf der Spur: Forschungsdaten in den Geisteswissenschaften, in: O-Bib. Das Offene Bibliotheksjournal, Bd. 5/2, 2018, S. 142–162. https://doi.org/10.5282/o-bib/2018H2S142-162

Deutsche Forschungsgemeinschaft: DFG-Praxisregeln „Digitalisierung“, 2016, https://www.dfg.de/formulare/12_151/. Letzter Zugriff 28.02.2023

Digital Repository of Ireland (DRI), Research Data Alliance Ireland (RDA): Publishing GLAM data as FAIR data, Europeana Research Webinar, 2020, https://www.rd-alliance.org/publishing-glam-data-fair-data. Letzter Zugriff 28.02.2023

Easterday, Kelly / Paulson, Tim / DasMohapatra, Proxima / Alagona, Peter / Feirer, Shane / Kelly, Maggi: From the Field to the Cloud: A Review of Three Approaches to Sharing Historical Data From Field Stations Using Principles From Data Science, in: Frontiers in Environmental Science, 6, 2018, https://doi.org/10.3389/fenvs.2018.00088

FORCE11: Guiding Principles for Findable, Accessible, Interoperable and Re-usable Data Publishing version b1.0, 2011/2021, https://force11.org/info/guiding-principles-for-findable-accessible-interoperable-and-re-usable-data-publishing-version-b1-0/. Letzter Zugriff 28.02.2023

Go FAIR, https://www.go-fair.org/. Letzter Zugriff 28.02.2023

Higman, Rosie / Bangert, Daniel / Jones, Sarah: Three Camps, One Destination: The Intersections of Research Data Management, FAIR and Open, in: Insights 32 (1), 18, http://doi.org/10.1629/uksg.468

Kraft, Angelina: Die FAIR Data Prinzipien für Forschungsdaten, in: TIB Blog, 2017, https://blogs.tib.eu/wp/tib/2017/09/12/die-fair-data-prinzipien-fuer-forschungsdaten/. Letzter Zugriff 28.02.2023

Hollander, Hella / Morselli, Francesca / Uiterwaal, Frank / Admiraal, Femmy / Trippel, Thorsten / Di Giorgio, Sara: PARTHENOS Guidelines to FAIRify data management and make data reusable, 2019, https://doi.org/10.5281/zenodo.3368858

PARTHENOS – Pooling Activities, Resources and Tools for Heritage E-research Networking, Optimization and Synergies, Horizon 2020-EU.1.4.1.1. (2015–2019), https://www.parthenos-project.eu/. Letzter Zugriff 28.02.2023

RDA FAIR Data Maturity Model Working Group: FAIR Data Maturity Model. Specification and guidelines (engl.), 2020, https://doi.org/10.15497/RDA00050 und dies.: Das FAIR Data Maturity Model. Spezifikation und Leitlinien (dt.), 2020, https://doi.org/10.5281/zenodo.5834115

Schöch, Christof: Big? Smart? Clean? Messy? Data in the Humanities, in: Journal of Digital Humanities Volume 2, Issue 3, 2–13, 2013, https://nbn-resolving.org/urn:nbn:de:bvb:20-opus-129492

Smedt, Koenraad / Koureas, Dimitrios / Wittenburg, Peter: FAIR Digital Objects for Science: From Data Pieces to Actionable Knowledge Units, in: Publications, 2020, 8(2), 21, https://doi.org/10.3390/publications8020021

Wilkinson, Mark D. / Dumontier, Michel / Aalbersberg, IJsbrand Jan et al.: The FAIR Guiding Principles for scientific data management and stewardship, in: Scientific Data 3, 160018 EP, 2016, https://doi.org/10.1038/sdata.2016.18

Zeng, Marcia Lei / Qin, Jian: Metadata, 3. Aufl., 2022