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2010 | OriginalPaper | Chapter

Ontological Primitives for Visual Knowledge

Authors : Alexandre Lorenzatti, Mara Abel, Sandro Rama Fiorini, Ariane Kravczyk Bernardes, Claiton Marion dos Santos Scherer

Published in: Advances in Artificial Intelligence – SBIA 2010

Publisher: Springer Berlin Heidelberg

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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.

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Metadata
Title
Ontological Primitives for Visual Knowledge
Authors
Alexandre Lorenzatti
Mara Abel
Sandro Rama Fiorini
Ariane Kravczyk Bernardes
Claiton Marion dos Santos Scherer
Copyright Year
2010
Publisher
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/978-3-642-16138-4_1

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