Modern science has many unique challenges related to handling the unprecedented breadth and depth of data we are now able to consume with current tools and instruments. Researchers need lightweight, user friendly tools to capture, manage, and curate data throughout the scientific discovery process.

To that end, ISRD has developed the Discovery Environment for Relational Information and Versioned Assets (DERIVA) platform.

DERIVA is an asset management platform designed to support scientific collaboration through the full lifecycle of data - from early experiment design, to data acquisition, analyses and ultimately publication.

DERIVA offers flexibility, specificity and security for consuming practically any kind of data and connecting the dots between them to make them more discoverable and, ultimately, more useful to scientists.

Watch the DERIVA Overview Video (2 minutes).

 

DERIVA allows scientists, labs and organizations to:

• Ingest and effectively describe diverse scientific assets.
• Organize and discover assets via rich metadata models.
• Store and retrieve assets quickly and easily.
• Integrate and share data collections.
• Enforce rights management/access control as needed.

The following figure shows a high level view of DERIVA's architecture:

DERIVA is also highly configurable. The system can adapt to changes in the underlying data model, and the interfaces also allow customization of style, documentation links, navigation menus and more.

For more information:

• Learn about the different Technologies that make up the DERIVA platform.
• Check out the Scientific Projects and Coordinating Centers powered by DERIVA.

Related publications

• ERMrest: A web service for collaborative data management.
• Experiences with DERIVA: An Asset Management Platform for Accelerating eScience.
• Accelerating Data-driven Discovery with Scientific Asset Management
• ERMRest: An Entity-relationship Data Storage Service for Web-based, Data-oriented Collaboration
• I'll Take That to Go: Big Data Bags and Minimal Identifiers for Exchange of Large, Complex Datasets

DERIVA has been funded by the National Institute of Health (NIH) via grants 5U24DK110814, 1U01DK107350, 5U01DE024449, 5R01MH107238, 5U54EB020406, P41-EB015922 and the GPCR Consortium.