Knowledge Graphs

Tuesday, September 10, 2019 - 10:30 to 12:00


Knowledge Graphs: Fundamental concepts of linking data to knowledge

Thomas will introduce fundamental concepts of linking data to knowledge in order to empower – not only – subject matter experts to benefit from data and provide knowledge. By leveraging a W3C standards-based Semantic Web approach to the Linked Data life cycle we will understand how to bridge data silos, and manage and extract metadata in order to create entity centric and knowledge-based applications. We will look into search, analytics, and recommendation.

Knowledge Graph Implementation - inspire the users to support your approach!

Often the implementation of new approaches and technologies do not fail because the approach is wrong but user do not support new ways of doing things. How can you inspire your users to support the implementation of the Knowledge Graph technology in your organisation? Get valuable ingredients such as Workshop material, argumentation guidelines and hands on practices. Inspire your audience to support and understand what benefits they can take out of the semantic technology. Make it work and make it happen.

Building and Visualising Enterprise-Ready Knowledge Graphs in the Cloud

Oracle Spatial and Graph in Oracle Database is available in the Oracle Cloud Infrastructure (OCI). It delivers advanced RDF Graph data management and analysis, with native support for World Wide Web Consortium (W3C) standards: RDF, SKOS, OWL, and SPARQL, as well as native support for materialized entailments. Users benefit from the industry’s leading open, scalable graph data platform on Oracle Database with triple-level security, high performance, high scalability, and high availability.

eccenca Corporate Memory

eccenca Corporate Memory is a proven knowledge graph driven data solution for managing heterogeneous data from disparate data sources and creating exploitable Knowledge Graphs out of them.

The product demo will demonstrate three main aspects of eccenca Corporate Memory: 1) Dataset and vocabulary management 2) Data integration via mapping and linking of disparate data sources 3) Knowledge Graph exploration and exploitation