Zitationsvorschlag

Solanki, Dhwani et al.: Automated Metadata Extraction Compliant with Machine-actionable Software Management Plans, in Heuveline, Vincent et al. (Hrsg.): E-Science-Tage 2025: Research Data Management: Challenges in a Changing World, Heidelberg: heiBOOKS, 2025, S. 499–504. https://doi.org/10.11588/heibooks.1652.c23951

Lizenz (Kapitel)

Creative Commons License

Dieses Werk steht unter der Lizenz Creative Commons Namensnennung - Weitergabe unter gleichen Bedingungen 4.0 International.

Identifier (Buch)

https://doi.org/10.11588/heibooks.1652
ISBN 978-3-911056-51-9 (PDF)
ISBN 978-3-911056-52-6 (Softcover)

Veröffentlicht

05.11.2025

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Statistik

Autor/innen

Dhwani Solanki, Suhasini Venkatesh , Dietrich Rebholz-Schuhmann , Leyla Jael Castro

Automated Metadata Extraction Compliant with Machine-actionable Software Management Plans

Abstract: Research software and the FAIR for Research Software (FAIR4RS) principles are gaining more attention from research communities in different domains due to their role in the reproducibility of science. The Software Management Plans (SMPs) are a nice complement to the FAIR4RS principles and research software good practices. A machine-actionable layer providing semantically structured metadata describing the research software would make it easier for machines to process the data and would enable, for instance, the creation of Knowledge Graphs for research software metadata and related artifacts, e.g., data processed by the software. To this end, we have created the machine-actionable SMPs (maSMPs) metadata schema based on schema.org, and compatible with Bioschemas and Codemeta. To make it easier for researchers, we are also working on a tool to automatically extract such metadata from GitHub repositories. Here we introduce our approach towards maSMPs and present our preliminary work on automatic metadata extraction from GitHub API.

Keywords: Software Management Plans, machine-actionability, metadata