Ontological Primitives for Visual Knowledge
In the last few years, we have analyzed the best alternatives for acquiring and processing visual knowledge with the goal of supporting problem solving. We call visual knowledge the set of mental models that support the process of reasoning over information that comes from the spatial arrangement and visual aspects of entities. Also, visual knowledge is implicit, meaning that it is difficult to be explicitly represented solely with propositional constructs. In this paper, we describe a representational approach that helps geologists in capturing and applying this kind of knowledge, in order to support software development applied to interpretation tasks in Petroleum Geology applications. Our approach combines propositional constructs with visual pictorial constructs in order to model visual knowledge of geologists. These constructs are proposed in a strong formal model, founded by Formal Ontology concepts. Based on these constructs, we develop a full ontology for stratigraphic description of sedimentary facies. The Formal Ontology background and the approach are detailed and evaluated through the paper.
KeywordsSedimentary Structure Sedimentary Facies Domain Ontology Pictorial Representation Visual Knowledge
Unable to display preview. Download preview PDF.
- 1.Hudelot, C., Maillot, N., Thonnat, M.: Symbol Grounding for Semantic Image Interpretation: from image data to semantics. In: Tenth International Conference on Computer Vision. IEEE, Los Alamitos (2005)Google Scholar
- 2.Liu, Y., et al.: A Shape Ontology Framework for Bird Classification, in Digital Image Computing Techniques and Applications. In: 9th Biennial Conference of the Australian Pattern Recognition Society 2007, pp. 478–484 (2007)Google Scholar
- 4.Ullmann, S.: Semantics: An Introduction to the Science of Meaning. Rowman & Littlefield, Oxford (1979)Google Scholar
- 5.Guizzardi, G.: Ontological Foundations for Structural Conceptual Models, p. 410. Universal Press (2005)Google Scholar
- 6.Newell, A., Simon, H.A.: Human Problem Solving. Prentice-Hall, New Jersey (1972)Google Scholar
- 8.Gómez-Pérez, A., Fernández-López, M., Corcho, O.: Ontological Engineering. In: Wu, X., Jain, L. (eds.) Springer, London (2004)Google Scholar
- 10.Abel, M.: Estudo da perícia em petrografia sedimentar e sua importância para a engenharia de conhecimento. In: Programa de Pós-graduação em Computação, p. 239. Porto Alegre, UFRGS (2001)Google Scholar
- 12.Shimojima, A.: Operational constraints in diagrammatic reasoning. In: Logical Reasoning with Diagrams, pp. 27–48. Oxford University Press, Inc., Oxford (1996)Google Scholar