Works-magnet: Accelerating Metadata Curation for Open Science

TL;DR

Works-magnet is a tool that accelerates the curation of research metadata by combining automated AI calculations with human oversight, improving data quality for open science initiatives.

Contribution

It introduces an open-source platform that enhances metadata curation efficiency by integrating AI and human correction for diverse research data.

Findings

Improved metadata accuracy through AI-assisted correction.

Reduced human effort in metadata curation.

Enhanced open data quality for scientific research.

Abstract

The transition to Open Science necessitates robust and reliable metadata. While national initiatives, such as the French Open Science Monitor, aim to track this evolution using open data, reliance on proprietary databases persists in many places. Open platforms like OpenAlex still require significant human intervention for data accuracy. This paper introduces Works-magnet, a project by the French Ministry of Higher Education and Research (MESR) Data Science & Engineering Team. Works-magnet is designed to accelerate the curation of bibliographic and research data metadata, particularly affiliations, by making automated AI calculations visible and correctable. It addresses challenges related to metadata heterogeneity, complex processing chains, and the need for human curation in a diverse research landscape. The paper details Works-magnet's concepts, and the observed limitations, while outlining future directions for enhancing open metadata quality and reusability. The works-magnet app is open source on github https://github.com/dataesr/works-magnet