Bridging the Data Discovery Gap: User-Centric Recommendations for Research Data Repositories

Journal article

Despite substantial investment in research data infrastructure, data discovery remains a fundamental challenge in the era of open science. The proliferation of repositories and the rapid growth of deposited data have not resulted in a corresponding improvement in data findability. Researchers continue to struggle to find data that are relevant to their work, revealing a persistent gap between data availability and data discoverability. Without rich, high-quality metadata, robust and user-centred data discovery systems, and a deeper understanding of how different researchers seek and evaluate data, much of the potential value of open data remains unrealised. This paper presents a set of practical, evidence-based recommendations for data repositories and discovery service providers aimed at improving data discoverability for both human and machine users. These recommendations emphasise the importance of 1) understanding the search needs and contexts of data users, 2) addressing the roles that data repositories play in enhancing metadata quality to meet users’ data search needs, and 3) designing discovery interfaces that support effective and diverse search behaviours. By bridging the gap between data curation practices, discovery system design, and user-centred approaches, this paper argues for a more integrated and strategic approach to data discovery.

Authors: Wu, M; Löffler, F; Mathiak, B; Psomopoulos, F; Schindler, U

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Ubiquity Press
• Journal: Data Science Journal
• Volume: 25
• Pages: 6
• Publication date: 2026-02-12
• DOI: 10.5334/dsj-2026-006
• EISSN: 1683-1470
• ISSN: 1683-1470
• Language: English
• Keywords: Data quality; Metadata; Discoverability; Knowledge extraction; Open research; Bridging (networking); Data discovery; Data curation; Data element; Open data