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Key Researcher Talk – Supporting complex decision making by semantic technologies by Stefan Fenz (Remote)

June 21, 2021
2:00 pm - 2:30 pm

Join the 6th edition of our Key Researcher Talk Series!

Supporting complex decision making by semantic technologies

Complex decisions require stakeholders to identify potential decision options and collaboratively select the optimal option. Identifying potential decision options and communicating them to stakeholders is a challenging task as it requires the translation of the decision option’s technical dimension to a stakeholder-compliant language which describes the impact of the decision (e.g., financial, political). Existing knowledge-driven decision support methods generate decision options by automatically processing available data and knowledge. Ontology-based methods emerged as a sub-field in the medical domain and provide concrete instructions for given medical problems. However, the research field lacks an evaluated practical approach to support the full cycle from data and knowledge assessment to the actual decision making. This work advances the field by: (i) a problem-driven ontology engineering method which (a) supports creating the necessary ontology model for the given problem domain and (b) harmonizes relevant data and knowledge sources for automatically identifying decision options by reasoners, and (ii) an approach which translates technical decision options into a language that is understood by relevant stakeholders. Expert evaluations and real-world deployments in three different domains demonstrate the added value of this method.

Agenda

14:00 -14:30: Talk by Stefan Fenz (SBA Research)

Speaker

Stefan Fenz is key researcher at SBA Research and senior scientist at the TU Wien. Stefan’s research interests include organizational information security, semantic technologies and decision support.

Free Registration

Please reach out to us at events@sba-reserarch.org if you would like to join. The talk will take place online.

hosted by Vienna ACM SIGSAC Chapter.