Towards a general theory of action and time
Artificial Intelligence
Temporal logics in AI: semantical and ontological considerations
Artificial Intelligence
A critical examination of Allen's theory of action and time
Artificial Intelligence
Classical mereology and restricted domains
International Journal of Human-Computer Studies - Special issue: the role of formal ontology in the information technology
Parts, wholes, and part-whole relations: the prospects of mereotopology
Data & Knowledge Engineering - Special issue on modeling parts and wholes
Using Hierarchical Spatial Data Structures for Hierarchical Spatial Reasoning
COSIT '97 Proceedings of the International Conference on Spatial Information Theory: A Theoretical Basis for GIS
Reasoning about Binary Topological Relations
SSD '91 Proceedings of the Second International Symposium on Advances in Spatial Databases
RelMiCS'05 Proceedings of the 8th international conference on Relational Methods in Computer Science, Proceedings of the 3rd international conference on Applications of Kleene Algebra
Rough Mereology in Information Systems with Applications to Qualitative Spatial Reasoning
Fundamenta Informaticae
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Spatial information is information bound to spatial entities such as regions. It is based on the spatial structure alone (the valley includes the field) or connects thematic predicates with spatial entities (Joan Smith owns the field). Formal models of spatial information are concerned with the question of how the structure of space is related to inferences about spatial information. Therefore, in addition to formal models of the structure of space, formal models of the interrelation between thematic information and spatial entities have to be developed. This article addresses the relation between regions and thematic information. It presents a calculus of spatial predicators that is coping with qualitative distinctions, i.e., the mereological and topological structure of space. The spatial structure is given by the Closed Region Calculus, which provides the same terminology as RCC, but has finite models. The spatial predication calculus specifies the interaction of the spatial structure with the thematic information and provides a flexible tool for the representation of and inferences on spatial information.