SMECS: A Software Metadata Extraction and Curation Software

TL;DR

The paper introduces SMECS, a tool that bridges metadata extraction from sources like GitHub with a user-friendly curation interface to produce CodeMeta-based metadata, addressing the labor-intensive FAIRification of research software. It builds on HERMES harvesters to extract and merge metadata, offering an interactive curation phase and CodeMeta export, and demonstrates strong usability via a SUS score averaging 92.08. The study shows SMECS is highly usable and interoperable with existing tooling, while outlining opportunities to expand extraction, exports, and domain-specific schemas. Overall, SMECS reduces metadata creation effort, enhances findability and reusability of research software, and sets a foundation for broader integration with registries and knowledge graphs.

Abstract

Metadata play a crucial role in adopting the FAIR principles for research software and enables findability and reusability. However, creating high-quality metadata can be resource-intensive for researchers and research software engineers. To address this challenge, we developed the Software Metadata Extraction and Curation Software (SMECS) which integrates the extraction of metadata from existing sources together with a user-friendly interface for metadata curation. SMECS extracts metadata from online repositories such as GitHub and presents it to researchers through an interactive interface for further curation and export as a CodeMeta file. The usability of SMECS was evaluated through usability experiments which confirmed that SMECS provides a satisfactory user experience. SMECS supports the FAIRification of research software by simplifying metadata creation.

Figures (5)

• Figure 1: Phases of SMECS
• Figure 2: SMECS landing page for the start phase
• Figure 3: Process diagram: Extracting metadata through using HERMES
• Figure 4: SMECS curation page
• Figure 5: SUS scores for SMECS usability experiment as box plot