"Streamlining Data Publication: Automatic Metadata and Large Datasets in the Age of AI." Discussion Session at Open Science Conference 2025

This is a presentation of the discussion session "Streamlining Data Publication: Automatic Metadata and Large Datasets in the Age of AI" created by the DiTraRe team for the Open Science Conference in Hamburg 2025. Research data repositories are essential infrastructure for enabling Open Science and ensuring data is Findable, Accessible, Interoperable, and Reusable (FAIR). However, researchers working on repositories face significant challenges in handling ever-increasing volumes of large datasets and the often time-consuming manual process of creating comprehensive, quality metadata. These issues can hinder data publication workflows and limit the findability and usability of valuable research output. We will present the challenges encountered, propose solutions and first implementations for automatic metadata extraction and large data handling, and discuss how these innovations contribute to a more streamlined and scalable data publication workflow. Participants will have the opportunity to engage with developers and users of repositories, explore the practical implications for their own data management practices, and discuss the potential for adopting similar solutions in other repository contexts. This discussion session will provide insights into the approaches, technologies, and lessons learned from the Leibniz Science Campus “Digital Transformation of Research” (DiTraRe) work on RADAR and implementation of AI methods in the topic of metadata standardisation. The session is especially relevant for everyone interested in the practical implementation of advanced research data management features that promote reproducibility, efficiency and FAIR principles.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-10-08
DOI
https://doi.org/10.5281/zenodo.17281938
Primary Topic
Fern and Epiphyte Biology
Type
article
Field-Weighted Citation Impact
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article

"Streamlining Data Publication: Automatic Metadata and Large Datasets in the Age of AI." Discussion Session at Open Science Conference 2025

Zenodo (CERN European Organization for Nuclear Research)
Fern and Epiphyte Biology
article

"Streamlining Data Publication: Automatic Metadata and Large Datasets in the Age of AI." Discussion Session at Open Science Conference 2025

article en

Abstract

This is a presentation of the discussion session "Streamlining Data Publication: Automatic Metadata and Large Datasets in the Age of AI" created by the DiTraRe team for the Open Science Conference in Hamburg 2025. Research data repositories are essential infrastructure for enabling Open Science and ensuring data is Findable, Accessible, Interoperable, and Reusable (FAIR). However, researchers working on repositories face significant challenges in handling ever-increasing volumes of large datasets and the often time-consuming manual process of creating comprehensive, quality metadata. These issues can hinder data publication workflows and limit the findability and usability of valuable research output. We will present the challenges encountered, propose solutions and first implementations for automatic metadata extraction and large data handling, and discuss how these innovations contribute to a more streamlined and scalable data publication workflow. Participants will have the opportunity to engage with developers and users of repositories, explore the practical implications for their own data management practices, and discuss the potential for adopting similar solutions in other repository contexts. This discussion session will provide insights into the approaches, technologies, and lessons learned from the Leibniz Science Campus “Digital Transformation of Research” (DiTraRe) work on RADAR and implementation of AI methods in the topic of metadata standardisation. The session is especially relevant for everyone interested in the practical implementation of advanced research data management features that promote reproducibility, efficiency and FAIR principles.

Zenodo (CERN European Organization for Nuclear Research)
Karlsruhe Institute of Technology (DE), FIZ Karlsruhe – Leibniz Institute for Information Infrastructure (DE)
Industry, innovation and infrastructure
Openalex Percentile: Top 37%
Fern and Epiphyte Biology
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