HeFDI Data Week: FAIRly Simple – How can generative AI Support FAIR RDM?

FAIR Research Data Management in interdisciplinary large-scale projects is very challenging. Data formats, acquisition processes, and infrastructure are highly heterogeneous. Furthermore, many tasks in FAIR RDM are tedious and complex for the researchers. This talk will discuss the potentials of generative AI to support FAIR RDM on examples from a large-scale project.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-27
DOI
https://doi.org/10.5281/zenodo.15422345
Primary Topic
Research Data Management Practices
Type
article
Field-Weighted Citation Impact
0.00
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article

HeFDI Data Week: FAIRly Simple – How can generative AI Support FAIR RDM?

Zenodo (CERN European Organization for Nuclear Research)
Research Data Management Practices
article

HeFDI Data Week: FAIRly Simple – How can generative AI Support FAIR RDM?

article en

Abstract

FAIR Research Data Management in interdisciplinary large-scale projects is very challenging. Data formats, acquisition processes, and infrastructure are highly heterogeneous. Furthermore, many tasks in FAIR RDM are tedious and complex for the researchers. This talk will discuss the potentials of generative AI to support FAIR RDM on examples from a large-scale project.

Zenodo (CERN European Organization for Nuclear Research)
Fraunhofer Institute for Applied Information Technology (DE), RWTH Aachen University (DE)
Industry, innovation and infrastructure
Openalex Percentile: Top 32%
Research Data Management Practices
DOIOpen Access PDFOpenAlex
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HeFDI Data Week: FAIRly Simple – How can generative AI Support FAIR RDM? · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS