Tech tutorials pre-event will be offered by Metaphacts, Microsoft, and Databricks one week before the event.

Tutorial Metaphacts – 23.09.2022 at 5 pm – online session.

Title: Explicit knowledge modeling for AI-driven decision making 

Abstract: Artificial Intelligence – be it data-driven or explicit AI – has the potential to revolutionize the way we work. A form of explicit AI, knowledge graphs deliver connected insights across functional or use case boundaries and drive knowledge democratization in the enterprise. Because they support the explicit modeling of knowledge traditionally hidden in complex processes, long documents, domain-specific applications, or domain experts’ minds, they are a great foundation for trustworthy and explainable business decisions and processes.

In this tutorial, we will present the gold standard approach to explicit knowledge modeling (semantic modeling) which transforms the creation of a knowledge graph into a streamlined, end-to-end process where all relevant stakeholders – from IT experts and ontology engineers to domain experts and business users – are equally involved. This approach is based on metaphactory’s visual and user-friendly interface for creating, exploring, visualizing, editing, and documenting knowledge graph assets such as ontologies, taxonomies, or data catalogs. The visual language translates to core elements of OWL, SHACL and SKOS and results in knowledge graph assets based on open and flexible W3C standards.

To make the tutorial as use case driven as possible, we will look at explicit knowledge modeling in the context of skill management and will cover the following topics:

  • Visual creation of OWL/SHACL ontologies which allows business users and domain experts to contribute to the ontology engineering process.
  • Creation and management of SKOS taxonomies which allows business users and domain experts to capture business-relevant terms in organized vocabularies.
  • Data catalog integration – Creation, management and import of existing dataset metadata at integration time.
  • Creating a model-driven end-user interface for all business users to look up, explore and discover knowledge stored in the knowledge graph.
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