About ICA Records in Contexts Ontology (RiC-O)

An information website about Records in Contexts Ontology (RiC-O).

View the Project on GitHub ICA-EGAD/RiC-O

About RiC-O

Last updated on February 1st, 2024

RiC-O (Records in Contexts-Ontology) is an OWL 2 ontology for describing archival record resources. As the third part of Records in Contexts (RiC) standard, it is a formal representation of Records in Contexts Conceptual Model (RiC-CM).

The latest public release of RiC-O, RiC-O 1.0, was published in December 2023. It is fully documented in English and available in the RiC-O GitHub repository, in the current-version folder. It replaces RiC-O 0.2, which was released in February 2021. It comes with some examples and diagrams.

RiC-O 1.0 is compliant with the latest version of Records in Contexts-Conceptual Model (RiC-CM), RiC-CM 1.0, which was released in November 2023 and is available for download is available for download here, or from the ICA website.

The version 1.0 of RiC-FAD, RiC-CM, and RiC-O marks the first stable and complete version of the first three parts of RiC, and thus a major milestone in the development of the standard.

RiC standard is developed by the International Council on Archives Expert Group on Archival Description (ICA EGAD).

RiC makes it possible to describe archival records and the multiple layers of contexts in which they are inscribed through time, from their creation to their curation in an archival institution. It enables archivists and records managers to move forward, from the four previous ICA description standards (ISAD(G), ISAAR(CPF), ISDF and ISDIAH), which it replaces, to a more accurate, more nuanced, easier to process, multidimensional description.

RiC-O provides a generic vocabulary and formal rules for creating RDF datasets (or generating them from existing archival metadata) that describe in a consistent way any kind of archival record resource and its contextual entities. It is therefore a reference model for publishing archival metadata sets as Linked Data, querying them using SPARQL, and making inferences using the logic of the ontology.

If you want to contact us, or send comments and questions, use the new Records in Contexts users Google group. Or directly create issues, or comments to existing issues, on GitHub.