Krzysztof Janowicz

Krzysztof Janowicz

CRML Affiliated Faculty

Professor, Geographic Information Science and Geoinformatics



Professor Janowicz is interested in the formal representation of spatial and geographic knowledge both on the level of individual statements, e.g., measurements, as well as the schemata used to categorize these statements, e.g., using geographic feature types. He works on top-down axiomatizations, i.e., formal specification, as well as on learning representations bottom-up. In this context, Janowicz works on the conceptual foundations of knowledge graphs and their applications to a wide range of problems in the broader earth sciences. He is particularly interested in urban spaces and places of interest, more specifically. As director of the Center for Spatial Studies, Janowicz also explores how space and time act as fundamental principles for knowledge organizations across academic disciplines.


My name is Krzysztof Janowicz. I am a (full) professor for Geographic Information Science and Geoinformatics at the Geography Department of the University of California, Santa Barbara, USA. I am the program chair of the Cognitive Science Program, associate director of the Center for Spatial Studies, one of two Editors-in-Chief of the Semantic Web journal, a Faculty Research Affiliate of the Center for Information Technology and Society, and the community leader of the 52° North semantics community. Finally, I am running the STKO Lab which investigates the role of space and time for knowledge organization. Before, I was an Assistant Professor at the GeoVISTA CenterDepartment of Geography at the Pennsylvania State University, USA. Before moving to the US, I was working as postdoctoral researcher at the Institute for Geoinformatics (ifgi), University of Münster in Germany for the international research training group on Semantic Integration of Geospatial Information and the Münster Semantic Interoperability Lab (MUSIL). Methodologically, my niche is the combination of theory-driven (e.g., semantics) and data-driven (e.g., data mining) techniques.