Remove Data Integration Remove Document Remove Knowledge Discovery Remove Reporting
article thumbnail

Are You Content with Your Organization’s Content Strategy?

Rocket-Powered Data Science

So, there must be a strategy regarding who, what, when, where, why, and how is the organization’s content to be indexed, stored, accessed, delivered, used, and documented. Labeling, indexing, ease of discovery, and ease of access are essential if end-users are to find and benefit from the collection. Do not forget the negations.

Strategy 266
article thumbnail

Bridging the Gap Between Industries: The Power of Knowledge Graphs – Part I

Ontotext

It can apply automated reasoning to extract further knowledge and make new connections between different pieces of data. This model is used in various industries to enable seamless data integration, unification, analysis and sharing. computer manufacturers are relying on knowledge graphs (and GraphDB) in their operations.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Top Graph Use Cases and Enterprise Applications (with Real World Examples)

Ontotext

Graphs boost knowledge discovery and efficient data-driven analytics to understand a company’s relationship with customers and personalize marketing, products, and services. However, this information is typically stored in disparate locations, often hidden within departmental documents or applications.

article thumbnail

GraphDB and metaphactory Part II: An RDF Database and A Knowledge Graph Platform in Action

Ontotext

often want to find information about a particular medical product, for example, if any serious adverse reactions have been reported for it. FROCKG (Fact Checking for Large Enterprise Knowledge Graphs) is a Eurostars-2 project that aims to develop efficient approaches to ensure the veracity of facts contained in enterprise knowledge graphs.

article thumbnail

The Semantic Web: 20 Years And a Handful of Enterprise Knowledge Graphs Later

Ontotext

17 years later, in the third edition of The Semantic Web for the Working Ontologist , authors Dean Allemang, Hedler and Gandon covered these same perspectives with one distilled explanation: The Semantic Web faces the problem of distributed data head-on. Read about schema.org and LOD in our Knowledge Hub ).