Stardog supports a set of techniques for unifying structured enterprise data – chiefly, Virtual Graphs, which let you declaratively map data into a Stardog knowledge graph and query it via Stardog in situ.

Virtual Graph Mappings Learn how to unify relational data in Stardog at query time. Page Contents Background Mapping to Nodes Mapping IRIs Mapping Literals Mapping to Triples Mapping Tables …

Mappings Virtual Graphs Map structured data declaratively into RDF Support for RDBMS, CSV, MongoDB, Cassandra Mapping is conceptual, so you can: Extract, transform, load (ETL) into RDF …

Stardog supports a set of techniques for unifying structured enterprise data, chiefly, Virtual Graphs which let you declaratively map data into a Stardog knowledge graph and query it via Stardog.

Stardog Mapping Syntax 2 (SMS2) is a way to represent virtual graph mappings that is designed to support a broader range of source data formats than R2RML, including semi-structured data sources …

The result? A central hub where all of your data is semantically connected and mapped. With Stardog, you can: Find, integrate, catalog, and share your metadata Mine structured, semi-structured, and …

Learn how to create and query virtual graphs over relational data in Stardog.

Stardog represents data from structured, semi-structured, and unstructured sources in graph to create a uniform data layer, enriched with the full context of data from every source.

Broad Data Support – Represent data from structured, semi-structured, and unstructured sources to create a uniform data layer Real-time Connectors – Access on-prem and cloud data to enrich the …

One of the most powerful features of BITES, our unstructured data ingestion system, is the ability to easily create domain-specific NLP pipelines that process and extract structured data from text. We …