DataStaR: Using the Semantic Web approach for Data Curation

Abstract

In disciplines as varied as medicine, social sciences, and economics, data and their analyses are essential parts of researchers’ contributions to their respective fields. While sharing research data for review and analysis presents new opportunities for furthering research, capturing these data in digital forms and providing the digital infrastructure for sharing data and metadata pose several challenges. This paper reviews the motivations behind and design of the Data Staging Repository (DataStaR) platform that targets specific portions of the research data curation lifecycle: data and metadata capture and sharing prior to publication, and publication to permanent archival repositories. The goal of DataStaR is to support both the sharing and publishing of data while at the same time enabling metadata creation without imposing additional overheads for researchers and librarians. Furthermore, DataStaR is intended to provide cross-disciplinary support by being able to integrate different domain-specific metadata schemas according to researchers’ needs. DataStaR’s strategy of a usable interface coupled with metadata flexibility allows for a more scaleable solution for data sharing, publication, and metadata reuse.