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Semi-Automatic Export of Electrophysiological Metadata to NFDI4Health Local Data Hubs: Use Case of Microneurography odML-Tables – A Technical Case Report
Mayra Roxana Elwes, Alina Troglio, Masoud Abedi, Martin Golebiewski, Frank Meineke, Toralf Kirsten, Barbara Namer, Oya Beyan, Ekaterina Kutafina
40 - 48
10.3233/SHTI240836
Research Article
Studies in Health Technology and Informatics
Volume 317: German Medical Data Sciences 2024
Abstract

Introduction:

The Local Data Hub (LDH) is a platform for FAIR sharing of medical research (meta-)data. In order to promote the usage of LDH in different research communities, it is important to understand the domain-specific needs, solutions currently used for data organization and provide support for seamless uploads to a LDH. In this work, we analyze the use case of microneurography, which is an electrophysiological technique for analyzing neural activity.

Methods:

After performing a requirements analysis in dialogue with microneurography researchers, we propose a concept-mapping and a workflow, for the researchers to transform and upload their metadata. Further, we implemented a semi-automatic upload extension to odMLtables, a template-based tool for handling metadata in the electrophysiological community.

Results:

The open-source implementation enables the odML-to-LDH concept mapping, allows data anonymization from within the tool and the creation of custom-made summaries on the underlying data sets.

Discussion:

This concludes a first step towards integrating improved FAIR processes into the research laboratory’s daily workflow. In future work, we will extend this approach to other use cases to disseminate the usage of LDHs in a larger research community.

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