Computational geometry: algorithms and applications
Computational geometry: algorithms and applications
Conceptual Spaces: The Geometry of Thought
Conceptual Spaces: The Geometry of Thought
Machine Learning
Toward the semantic geospatial web
Proceedings of the 10th ACM international symposium on Advances in geographic information systems
Comparing Images Using the Hausdorff Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Ontology and Geographic Objects: An Empirical Study of Cognitive Categorization
COSIT '99 Proceedings of the International Conference on Spatial Information Theory: Cognitive and Computational Foundations of Geographic Information Science
Introduction to MPEG-7: Multimedia Content Description Interface
Introduction to MPEG-7: Multimedia Content Description Interface
Towards a general theory of geographic representation in GIS
International Journal of Geographical Information Science
IEEE Internet Computing
Managing uncertainty and vagueness in description logics for the Semantic Web
Web Semantics: Science, Services and Agents on the World Wide Web
An Ontology for Grounding Vague Geographic Terms
Proceedings of the 2008 conference on Formal Ontology in Information Systems: Proceedings of the Fifth International Conference (FOIS 2008)
Reasoning about categories in conceptual spaces
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Conceptual Space Markup Language (CSML): Towards the Cognitive Semantic Web
ICSC '09 Proceedings of the 2009 IEEE International Conference on Semantic Computing
Conceptual situation spaces for semantic situation-driven processes
ESWC'08 Proceedings of the 5th European semantic web conference on The semantic web: research and applications
A metric conceptual space algebra
COSIT'09 Proceedings of the 9th international conference on Spatial information theory
Constructing Bodies and their Qualities from Observations
Proceedings of the 2010 conference on Formal Ontology in Information Systems: Proceedings of the Sixth International Conference (FOIS 2010)
Fuzzy extensions of OWL: Logical properties and reduction to fuzzy description logics
International Journal of Approximate Reasoning
Semantic referencing - determining context weights for similarity measurement
GIScience'10 Proceedings of the 6th international conference on Geographic information science
Ontologies of geographic information
International Journal of Geographical Information Science
The Semantic Web needs more cognition
Semantic Web
ICCS'05 Proceedings of the 13th international conference on Conceptual Structures: common Semantics for Sharing Knowledge
Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
RW'13 Proceedings of the 9th international conference on Reasoning Web: semantic technologies for intelligent data access
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The semantic integration of heterogeneous, spatiotemporal information is a major challenge for achieving the vision of a multi-thematic and multi-perspective Digital Earth. The Semantic Web technology stack has been proposed to address the integration problem by knowledge representation languages and reasoning. However approaches such as the Web Ontology Languages (OWL) were developed with decidability in mind. They do not integrate well with established modeling paradigms in the geosciences that are dominated by numerical and geometric methods. Additionally, work on the Semantic Web is mostly feature-centric and a field-based view is difficult to integrate. A layer specifying the transition from observation data to classes and relations is missing. In this work we combine OWL with geometric and topological language constructs based on similarity spaces. Our approach provides three main benefits. First, class constructors can be built from a larger palette of mathematical operations based on vector algebra. Second, it affords the representation of prototype-based classes. Third, it facilitates the representation of classes derived from machine learning classifiers that utilize a multi-dimensional feature space. Instead of following a one-size-fits-all approach, our work allows one to derive contextualized OWL ontologies by reification of observation data.