KI.produktiv 2022

On September 19, 2022, metaphacts CEO, Sebastian Schmidt, will be giving a presentation at KI.produktiv 2022 during which he will discuss how explicit knowledge modeling and Machine Learning can enable data-driven decision making.


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 powering trustworthy, understandable, and explainable ML models. Ultimately, this helps deliver end-to-end decision intelligence solutions that provide contextual analytics, decision support, as well as continuous intelligence and decision automation.


In his session at KI.produktiv 2022, Sebastian 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. To make the session as practical as possible, he will use an example from skill management to demonstrate how graph AI can be used to answer questions such as:

  • What are relevant competencies for a business problem?
  • Which technological developments & innovations do I need watch?
  • Who in my organization has the required skills/expertise for a given task?
  • What are competency areas that I need to develop in my organization?
  • How should I compose my team for a given task?
  • What experience from previous projects can we leverage?

Session details at a glance

  • Title: Competency management with knowledge graphs: Enabling data-driven decisions with explicit knowledge modeling and Machine Learning
  • Track: AI & Business Models
  • Date: September 19, 2022