DERIVA is an innovative open-source scientific 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 can adapt to evolving and complex data models and data types. DERIVA supports continuous FAIRness by promoting self-curation, fine-grain access control, automated creation of global unique IDs for every data element, versioning, provenance, exchange of data through structured and documented data collections (BDBags).

DERIVA provides authentication, fine-grained authorization, secured access, and extensive logging. The authentication service works with many options, including the ability for users to authenticate with their NIH or home institutions via Globus Auth, which is an OAUTH2 authentication and authorization infrastructure widely used in NIH environments. DERIVA supports Globus Groups in fine-grained access policy.


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.

DERIVA combines a powerful entity-relationship database approach with a flexible, customizable user interface to link biomedical data and metadata to attributes users can find through search and filters in a familiar shopping-cart-like experience. DERIVA has been applied to diverse application domains.


Data intensive scientific discovery can be accelerated and collaboration enhanced when the data associated with the discovery are Findable, Accessible, Interoperable, and Reusable—the so called FAIR principals.

DERIVA promotes FAIR data production by:

  • F: providing rich metadata using an Entity-Relationship model to express relationships between diverse data elements;
  • A: offering rich access control and access to metadata via standard HTTP web service interfaces;
  • I: integrating with standardized terms defined by collaborators, consortium or communities; and
  • R: supporting dynamic model evolution so that the data presented accurately represents the current structure and state of knowledge within an investigation.