DiGIR is a protocol and a set of tools for linking a community of independent databases into a single, searchable “virtual” collection. The DiGIR protocol was developed by BRC Informatics in collaboration with the Museum of Vertebrate Zoology at UC Berkeley and the California Academy of Sciences. DiGIR is currently a public open source project with an international team of contributers, including Centro de Referência em Informação Ambiental (CRIA), Brazil.

DiGIR provides a uniform interface for managing XML-based search requests to a community of dissimilar data sources. Each institution in the DiGIR community implements an interface application called a DiGIR provider. The DiGIR provider hides the details of the underlying database and presents a uniform “virtual” view of the data to the network.

The DiGIR provider presents data in a common format independent of the underlying database.

When a user on the network types a search request, the client application sends a query in the virtual format. Each DiGIR provider translates the search request into an equivalent request compatible with the structure of the local database. When the DiGIR provider receives a response from the local database, it translates the response to match the virtual structure and sends the result to the client.

BRC uses DiGIR to search natural history collections for specimen and habitat data. This data is then used to produce an occurrence map showing where all the specimens of a particular species were found. The occurrence map is used by other applications, such as BRC’s DesktopGARP, to produce a distribution map showing the expected range of the species based on ecological factors such as temperature, precipitation, and cloud cover.

The DiGIR protocol evolved to replace the Z39.50 protocol used by an earlier BRC project, the Species Analyst and was first used effectively in MaNIS, a community of mammalian natural history collections. Since MaNIS, DiGIR has been integrated into a number of other collection community networks, such as GBIF, OBIS, ORNIS, and HerpNET.