Accelerating data-driven discovery with scientific asset management

The overhead and burden of managing data in complex discovery processes involving experimental protocols with numerous data-producing and computational steps has become the gating factor that determines the pace of discovery. The lack of comprehensive systems to capture, manage, organize and retrieve data throughout the discovery life cycle leads to significant overheads on scientists' time and effort, reduced productivity, lack of reproducibility, and an absence of data sharing. In “creative fields” like digital photography and music, digital asset management (DAM) systems for capturing, managing, curating and consuming digital assets like photos and audio recordings, have fundamentally transformed how these data are used. While asset management has not taken hold in eScience applications, we believe that transformation similar to that observed in the creative space could be achieved in scientific domains if appropriate ecosystems of asset management tools existed to capture, manage, and curate data throughout the scientific discovery process. In this paper, we introduce DERIVA, a framework and infrastructure for asset management in eScience and present initial results from its usage in active research use cases.