The Human Computer Studies (HCS) laboratory performs research on theories,
methods and technology regarding the design and use and evaluation of
complex human-computer systems.
A first class of complex human-computer systems that are object of study are knowledge-intensive
systems. Such systems can be based on human knowledge that is represented in ontologies
and knowledge bases, or can contain knowledge obtained by machine learning methods. This
research is centered around questions concerning semantic modeling, ontology engineering,
multi-agent systems and adaptive systems. Typical examples of such systems are: Semantic
Web applications, text mining tools, tools for developing and maintaining ontologies,
qualitative reasoning systems, adaptive systems and ontology population and learning
systems. Application domains include: cultural heritage, E-government services on the web,
knowledge management, modeling physical systems, intelligent learning environments,
bioinformatics, collaborative information management and virtual organizations.
A second class of complex human-computer systems that are object of study at HCS,
are e-learning environments, simulation environments for educational purposes and
interactive systems. A central topic is the study of interaction requirements and
user experiences, in particular for special user groups. Results of this research
include methods for requirement extraction, user evaluation methods and best practices.