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Free University of Bozen-Bolzano

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Knowledge and Data (KRDB)


We develop 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, and processes.

Covered Topics

  • Conceptual Modelling 
  • Semantic Interoperability 
  • Data Integration 
  • Data Preparation 
  • Intelligent Information System 
  • Ontologies 
  • Semantic Technologies 
  • Intelligent Querying Data 
  • Natural language interfaces to knowledge and data 
  • Knowledge Representation and Reasoning Systems 
  • Formal and Cognitive foundations of knowledge representation and reasoning 
    automated planning 
  • Modelling and Web Standards 
  • Reverse Engineering Data and Documents 
  • Reasoning and Verification with Temporal Data 
  • Computational Logic 

The research carried out in Knowledge and Data is organised into the following laboratories: 


Develops theoretical foundations and engineering tools for advancing representations of conceptualizations of reality with a focus on ontologically and cognitively adequate approaches and novel logical methods. Core topics are formal ontologies, non-classical logics, cognitive modelling, and multi-agent systems. 


Investigates both formal theories based on areas such as logic, discrete mathematics, and probability theory, as well as a wealth of technologies to store, access and manipulate large amounts of information. We tackle applications that present foundational challenges, either of conceptual or technological nature, to develop principled solutions and validate them. 


Investigates foundational, methodological, experimental, and application-oriented aspects of access to structured and semi-structured data and information by leveraging its semantics. We combine techniques developed in the area of knowledge representation and reasoning, with industrial technologies for the efficient management of large amounts of data. 


Conducts cutting-edge research at the intersection of artificial intelligence and dynamic systems, with a particular focus on business/work processes. We bridge theory and practice developing foundational and applied techniques grounded in artificial intelligence to tackle two major challenges: first, the development of intelligent agents and information systems that combine processes and data in an integrated way; second, the analysis of real event data for fact-based, continuous process improvement


The mission of the Smart Data Factory is to promote the technology transfer from academia to industry by implementing and adapting research results appropriately. This occurs through the transfer of advanced skills for the solution of complex problems in the areas of intelligent data, process, and software management and in the co-design and co-development of IT applications that exploit AI-based solutions.