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Free University of Bozen-Bolzano

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Knowledge and Data (KRDB)

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Coordinator

Oliver Kutz 

Members: Diego Calvanese, Enrico Franconi, Chiara Ghidini, Marco Montali, Werner Nutt, Alessandro Artale, Fabrizio Maria Maggi, Sergio Tessaris, Francesco Corcoglioniti, Julien Corman, Tiziano Dalmonte, Ivan Donadello, Mattia Fumagalli, Nicola Gigante, Davide Lanti, Andrea Mazzullo, Ognien Savkovic, Sarah Winkler

Description

KRDB studies foundational and applied techniques grounded in artificial intelligence, logics, and formal methods, to design, analyse, enact, and maintain intelligent information systems that combine data, information, knowledge, time, and processes. KRDB aims at confirming itself as a leading research group in knowledge-based AI research, education, and industry relations. KRDB is a green member of the Confederation of Laboratories for Artificial Intelligence Research in Europe (CLAIRE). The research topics in which KRDB is active are classified into four main parts: 

  • Knowledge Representation and Reasoning: the focus is on well-established approaches such as Description Logics, novel approaches like Knowledge Graphs, and their role as ontology languages. 
  • Knowledge and Data: the focus is on the impact of knowledge-based AI to data-intensive domains, and specifically on ontology-based data access, conceptual modelling, knowledge-based data management, knowledge-based data science, neuro-symbolic approaches to learning. 
  • Knowledge in Time and Processes: the focus includes temporal and action languages, process modelling, mining, and analysis, predictive process monitoring, and AI for process science. 
  • Knowledge and Cognition: the focus is on understanding how humans acquire, represent, and use knowledge, and the computational aspects of these cognitive processes: computational creativity, foundational ontologies, knowledge-based natural language processing, and multi-modal interfaces.