A semantic repository is an engine similar to a database management systems (DBMS) that permits the storage, querying and handling of structured data. In addition, a semantic repository uses ontologies as semantic schemata to automatically reason about the queried data. Semantic repositories make use of generic and flexible physical data models, such as graphs. This permits them to quickly read and implement new metadata schemata or ontologies. As a result, semantic repositories provide better incorporation of assorted data as well as more analytical power. However, these kinds of repositories are still in the early stages of their development.
Semantic repositories integrate the characteristics of inference engines and DBMS, and they function much like Web servers. Therefore, they can store, understand and serve requests from numerous users to substantial volumes of data.
Some of the major characteristics of semantic repositories are as follows:
Simple incorporation of numerous data sources
Simple and quick querying against diverse or rich data schemata
Significant analytical power that uncovers facts determined by interlinking long-chain evidences
Highly effective data interoperability
Semantic repositories can be used to fulfill various goals, such as:
Managing significant volumes of data
Accelerating loading, indexing and modification of data
Enabling quicker query analysis, or faster management of a single complex query
Enabling improved management of massive user volume and concurrent query loads
Sesame is a well-known semantic repository that supports RDF(S) and all query languages and key syntaxes associated with it. OWLIM is another popular semantic repository, which is offered as an inference and storage layer for Sesame. OWLIM works by using the TRREE engine to blend OWL DLP, RDFS, and OWL Horst support with superior analytics and dependable tolerance strategy.