Ontology Management

Ontology Management today has become
a truly enterprise-scale problem.

Here is the good news: The backbone of your enterprise ontologies already exists today – distributed across many data sources throughout your enterprise as well as within public ontologies. However, given the number of both internal and external sources of taxonomies and vocabularies addressing multiple domains, it is not possible to integrate and align that much data by manually documenting and organizing all the various terms and sharing them through traditional means.  The knowledge graph solves this problem by extracting terminologies from relevant data sources and then harmonizing them using standards models such as SKOS or OWL.  End users can curate and manage individual parts of these ontologies before publishing them out across the business at scale.

Ontology Management

Anzo supports enterprise-scale ontology management by:

Ontologies built with Anzo deliver vast collections of clean consistent data to fuel improved daily operations and richer analytic insights.

Case Study: Enterprise-Scale Ontology of Life Science Data

Merck KGaA is using Anzo as the platform for a large scale ontology that manages all the data they use for regulatory reporting globally.

Learn More

The Business Case for Semantic Web Ontology & Knowledge Graph

Explore the benefits of building a Semantic Knowledge Graph with RDF*

Learn More

Semantic Web for the Working Ontologist

Fireside Chat with Authors Dean Allemang, Jim Hendler and Fabien Gandon

Learn More

6 Essential Requirements for a Knowledge Graph

Scalability, flexibility, and interoperability. Learn how Anzo supports key requirements of ontology projects.

Learn More