BittnerDonnelly
Spatial Ontology and Qualitative Reasoning
July 20-21, 2009
Two-day Course organized as part of the Buffalo Ontology Week
Faculty: Thomas Bittner and Maureen Donnelly This course will provide an introduction to a variety of theories developed for representing and reasoning about spatial relations among entities in the worldand. it will provide students with the tools for developing their own spatial ontologies. Theories treated will include:
- i) mereotopologies (theories of parthood and connection relations),
- ii) theories of ordering relations,
- iii) theories of distance relations.
We will examine also more complex spatial theories which introduce topics such as granularity, change in spatial relations over time, and spatial relations among classes of individuals.
Literature P. M. Simons, Parts: A Study in Ontology, Oxford: Clarendon Press, 1987. R. Casati and A. Varzi, Parts and Places: The Structures of Spatial Representation, Cambridge, MA: MIT Press, 1999.
Thomas Bittner is Assistant Professor in the Departments of Philosophy and Geography at the State University of New York at Buffalo. He is also Research Scientist in the New York State Center of Excellence in Bioinformatics and Life Sciences and in the National Center of Geographic Information and Analysis (NCGIA). Dr. Bittner received his Ph.D. from the Technical University Vienna and has been a postdoctoral researcher at Northwestern University and at Queen’s University (Canada). Before joining the SUNY Buffalo he was a senior researcher at the Institute for Formal Ontology and Medical Information Science (IFOMIS) at Saarland University in Germany. Dr. Bittner’s area of specialization is formal ontology and its applications in bio-informatics, geography, and geographic information science. His current research focuses on the application of formal ontology, symbolic logic, and qualitative representation and reasoning techniques (a) to represent canonical biomedical structures in biomedical ontologies, (b) to detect pathological structures in medical image analysis, and (c) to develop axiomatic theories of biomedical structures and processes across different levels of granularity.