Abstract
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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
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)
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)
Bertini, M., et al.: Dynamic pictorial ontologies for video digital libraries annotation. In: MS 2007: Workshop on Multimedia Information Retrieval on the Many Faces of Multimedia Semantics, pp. 47–56. ACM, New York (2007)
Ullmann, S.: Semantics: An Introduction to the Science of Meaning. Rowman & Littlefield, Oxford (1979)
Guizzardi, G.: Ontological Foundations for Structural Conceptual Models, p. 410. Universal Press (2005)
Newell, A., Simon, H.A.: Human Problem Solving. Prentice-Hall, New Jersey (1972)
Guarino, N.: Formal ontology, conceptual analysis and knowledge representation. International Journal Human-Computer Studies 43(2/3), 625–640 (1995)
Gómez-Pérez, A., Fernández-López, M., Corcho, O.: Ontological Engineering. In: Wu, X., Jain, L. (eds.) Springer, London (2004)
Guarino, N., Welty, C.A.: An overview of OntoClean. In: Staab, S., Studer, R. (eds.) Handbook of Ontologies, pp. 151–171. Springer, Heidelberg (2004)
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)
Abel, M., et al.: Knowledge acquisition and interpretation problem-solving methods for visual expertise: a study of petroleum-reservoir evaluation. Journal of Petroleum Science and Engineering 47(1/2), 51–69 (2005)
Shimojima, A.: Operational constraints in diagrammatic reasoning. In: Logical Reasoning with Diagrams, pp. 27–48. Oxford University Press, Inc., Oxford (1996)
Lorenzatti, A., et al.: Ontology for Imagistic Domains: Combining Textual and Pictorial Primitives. In: Heuser, C.A., Pernul, G. (eds.) ER 2009 Workshops. LNCS, vol. 5833, pp. 169–178. Springer, Heidelberg (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lorenzatti, A., Abel, M., Fiorini, S.R., Bernardes, A.K., dos Santos Scherer, C.M. (2010). Ontological Primitives for Visual Knowledge. In: da Rocha Costa, A.C., Vicari, R.M., Tonidandel, F. (eds) Advances in Artificial Intelligence – SBIA 2010. SBIA 2010. Lecture Notes in Computer Science(), vol 6404. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16138-4_1
Download citation
DOI: https://doi.org/10.1007/978-3-642-16138-4_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16137-7
Online ISBN: 978-3-642-16138-4
eBook Packages: Computer ScienceComputer Science (R0)