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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. This can lead to operational cost cutting and improve competitiveness.

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

Ontotext

However, although some ontologies or domain models are available in RDF/OWL, many of the original datasets that we have integrated into Ontotext’s Life Sciences and Healthcare Data Inventory are not. Additionally the level of standardization, integration and normalization in these datasets is of varying quality.

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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.