Vision collage_siteThe Center for Spatial Studies focuses on promoting spatial thinking and spatial analytics across academia, industry, and government agencies, and across disciplines ranging from the humanities to the physical sciences with particular focus on novel Spatial Data Science methods and Knowledge Graphs.  For example,  the center has expertise in spatiotemporally-explicit machine learning, in the formal representation of spatial phenomena including but not limited to geographic space, knowledge engineering, as well as in methods to improve the publication, retrieval, reuse, and integration of heterogeneous data across domain boundaries.

Following the insight that understanding when and where things happen is key to understanding why they happened or will happen, our vision is to demonstrate how (geographic) space and time act as convergence catalysts to integrate heterogeneous data across domains to answer complex social and scientific questions that cannot be answered from within one domain alone. Our mission is to develop spatially and temporally explicit techniques for the creation, filtering, linkage, synthesis, prediction, and forecasting of information in large-scale, cross-domain data repositories and knowledge graphs. 

Beyond that, the Center’s research activities include:

A full listing of our activities is summarized in the Center for Spatial Studies Activity Reports, which were published in 2010, 2013, 2016, and 2020.

We strongly encourage you to discuss your research and educational projects with us, to further our collective understanding and awareness of the importance of spatial thinking and computing across disciplines.