The knowledge graph (KG) represents a shared conceptualization across the organization describing all-important business objects and concepts, their relations and metadata. Unlike traditional data warehouse systems, the KG organizes and unites diverse master data, reference data and metadata. Knowledge graphs are based on W3C standards, like RDF(S) and OWL, so they can guarantee a true application-independent and knowledge-centric approach with a self-describing schema.
The formal semantics of RDFS and OWL allow enterprises to have strict definitions, allowing both human experts and machines to interpret unambiguously data collected from different sources. What is even more attractive, enterprises can augment their knowledge graphs by applying inference to uncover new information. The resulting KG will have more data than the sum of its constituent datasets. It is also better interconnected and allows faster discovery of multi-hop relationships and patterns. This way users get richer sets of relevant results in less time.
While automatic reasoning has always inspired the imagination, numerous projects have failed to deliver to the promises. The typical pitfalls related to ontologies and symbolic reasoning fall into two categories:
The webinar will provide a brief introduction to logical reasoning and overview of the most popular semantic schema and ontology languages: RDFS and the profiles of OWL 2. We will demonstrate how reasoning works on FactForge – our public GraphDB demonstration service, exposing a knowledge graph of more than 2 billion statements, combining DBPedia, GeoNames, FIBO and other data. Next, we will introduce the different reasoning implementation approaches and discuss their fitness for specific application scenarios. Finally, we will provide a quick guidance for configuration and customization of reasoning with GraphDB.
In this webinar you will learn:
Who is this webinar for:
Atanas Kiryakov is the founder and CEO of Ontotext and member of the board of the Linked Data Benchmarking Council – standardization body, who's members include the major graph database vendors. Kiryakov obtained his M.Sc. degree in AI from the Sofia University, Bulgaria, in 1995. Today he is a top expert in semantic graph databases, reasoning, knowledge graphs, text mining, semantic tagging, linking and search. Author of signature academic publications with more than 2500 citations. Atanas is partner and board member in Sirma Group Holding – one of the biggest Bulgarian IT businesses, listed at the Sofia Stock Exchange. Atanas started in Sirma as software engineer in 1993 and became a partner in 1997. In the 90s he has led projects in the areas of CASE, CSCW, and b2b for big corporations and government organizations in US and Canada.