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Other literature type . 2026
License: CC BY
Data sources: ZENODO
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Presentation . 2026
License: CC BY
Data sources: Datacite
ZENODO
Presentation . 2026
License: CC BY
Data sources: Datacite
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Research Data Management with Machine Training Support

Authors: Möller, Ralf;

Research Data Management with Machine Training Support

Abstract

Abstract from the author In the age of digital science more and more information systems based on curated data for a certain research field become available. Scholars can use information systems to analyze data and draw conclusions, which are then written down in scientific publications. Arguments contained in the publications can, however, usually be tied to data with a lot of effort only. Visualizations for scholars, for instance, in particular 3D visualizations with immersion effects, although very valuable for getting insights, can hardly be made available with current technology in such a way that other researchers can indeed verify the arguments that a scholar derived from 3D display elements (and more conventional display elements) shown in information systems. Pictures and videos that are usually referred to are no longer enough for scientific argumentation in the digital age. The presentation discusses the current state-of-the-art in scientific information systems and provided new ideas for combining data display, citation, and verification of arguments using formal means. Background: The published presentation was part of a talk (29/04/2026) organized by the State Initiative Research Data Management Lower Saxony (FDM-NDS), the Leibniz Information Centre for Science and Technology University Library (TIB) and in cooperation with NFDI4Culture. FDM-NDS is a collaborative project under the umbrella of Hochschule.digital Niedersachsen and is funded as part of zukunft.niedersachsen, a funding program from the Lower Saxony Ministry of Science and Culture (MWK) and VolkswagenStiftung.

Related Organizations
Keywords

citation, annotation, RDM, research data management, 3D objects

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green