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Scientific discovery is increasingly dependent on a scientist's ability toacquire, curate, integrate, analyze, and share large and diverse collections ofdata. While the details vary from domain to domain, these data often consist ofdiverse digital assets (e.g. image files, sequence data, or simulation outputs)that are organized with complex relationships and context which may evolve overthe course of an investigation. In addition, discovery is often collaborative,such that sharing of the data and its organizational context is highlydesirable. Common systems for managing file or asset metadata hide theirinherent relational structures, while traditional relational database systemsdo not extend to the distributed collaborative environment often seen inscientific investigations. To address these issues, we introduce ERMrest, acollaborative data management service which allows general entity-relationshipmodeling of metadata manipulated by RESTful access methods. We present thedesign criteria, architecture, and service implementation, as well as describean ecosystem of tools and services that we have created to integrate metadatainto an end-to-end scientific data life cycle. ERMrest has been deployed tohundreds of users across multiple scientific research communities and projects.We present two representative use cases: an international consortium and anearly-phase, multidisciplinary research project.

ERMrest: an entity-relationship data storage service for web-based, data-oriented collaboration