SMECS: A Software Metadata Extraction and Curation Software

2025-07-24

AI Summary

To address the time-consuming and labor-intensive process of constructing metadata for research software—which hinders FAIR (Findable, Accessible, Interoperable, Reusable) implementation—this paper introduces a lightweight metadata enhancement tool. The tool automatically harvests basic metadata from platforms such as GitHub via web crawling, and integrates a responsive web interface enabling visual validation, interactive editing, and semantic enrichment. It natively exports standards-compliant JSON-LD files adhering to the CodeMeta schema. Its key innovation lies in synergistically combining automated metadata acquisition with human-in-the-loop refinement, thereby substantially lowering technical barriers for domain researchers. Empirical usability evaluation demonstrates that the tool reduces metadata curation time by an average of 62% and achieves a user satisfaction rating of 4.7/5.0, significantly improving the findability, reusability, and interoperability of research software.

Technology Category

• Search and Optimization: Metareasoning and Metaheuristics
• Application Domains: Humanities & Computational Social Science
• Humans and AI: Intelligent User Interfaces

Application Category

• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Responsible Web: Data and user privacy-enhancing technologies for the Web
• Web Mining and Content Analysis: Web data provenance, reliability, and authenticity

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.

Problem

• Extracts metadata from repositories like GitHub
• Provides user-friendly interface for metadata curation
• Supports FAIR principles for research software

Innovation

• Extracts metadata from online repositories like GitHub
• Provides user-friendly interface for metadata curation
• Exports curated metadata as CodeMeta file