GraphDB 9.1: Knowledge Graphs with Data Provenance

This webinar has been recorded and available on YouTube. Follow this link to access the recording.

Ontotext has recently announced the 9.1 release of GraphDB – the most powerful enterprise-ready database optimized for the development and operations of knowledge graphs.

In the last year, Google has popularized the term knowledge graph. What is a knowledge graph? It’s a semantic network describing entities and their relations with the help of a model that enables mathematical computations, also known as formal semantics. Why is this important? The knowledge graph model enables you to search for things versus strings. One of its many applications is natural language processing, where the knowledge graph can disambiguate with a much higher confidence score than other traditional methods. For example, it can tell you whether an article is about Georgia, the country, or the US state.

Despite the popularity of knowledge graphs, few organizations are implementing the technology successfully. In this webinar, we will show you how to develop a powerful enterprise knowledge graph with publicly accessible datasets and increase the digital dexterity of your organization. It will also enable you to make important business decisions based on harmonized knowledge models derived from siloed source systems.

The webinar lead will be Desislava Hristova, a Senior Software engineer at Ontotext.

In this webinar you will learn how to:

• Create a knowledge graph with data from different information sources;
• Automatically reconcile similar entities from multiple sources;
• Keep the graph up-to-date with data source updates;
• Track graph changes with GraphDB 9.1 new data history and versioning features

Who is this webinar for

•  Technical people confident in SPARQL;
•  Consultants and Solution Architects;
•  Linked Data Scientists.

Expected duration: 45 min

To watch the recording, follow this link.