Skip to main content

Records in Contexts (RiC)

Records in Contexts (RiC) is a data model and ontology developed by the Expert Group on Archival Description (EGAD) of the International Council on Archives (ICA). RiC has been designed as a new standard for describing archival context and aims to enhance the representation, exchange, and connection of archival information.

RiC Entities​

Records in Contexts identifies a total of 22 entities, which represent the main objects of interest for archivists that manage records retained for long-term preservation and access. These entities are those required to provide the context that serves physical management, preservation, discovery, use, and understanding of the records over the course of their history.

Of these 22 entities, four are at the very heart of an archive, as they describe the records and the contexts within which they emerge and are used over time.

Core entities of the RiC model

Some of these entities are created when needed, especially a record resource, which is added once its corresponding archival document is captured by archivist.

An instantiation represents a concrete physical or digital manifestation of a record resource — the actual object that carries the intellectual content in a specific form, format, or medium. A single record resource may have multiple instantiations; for example, an original paper document and its digitised copy are two distinct instantiations of the same record. Instantiations capture properties such as storage location, format, and extent that are tied to the specific carrier rather than to the intellectual content itself.

Controlled vocabularies​

Other entities, in particular places, agents and concepts, are typically pre-defined in controlled vocabularies, then linked with other entities. Such controlled vocabularies may be available locally or publicly.

As RiC uses standardised web technologies extensively, both public controlled vocabularies and public archival datasets form the cornerstone for building semantically rich and meaningful networks of linked, archival data. These networks may then be navigated, explored and processed by humans and machines alike.