Abstract
This work presents a study of the nature of expertise in geology, which demands visual recognition methods to describe and interpret petroleum reservoir rocks. In an experiment using rock ima ges we noted and analyzed how geologists with distinct levels of expertise described them. The study demonstrated that experts develop a wide variety of representations and hierarchies, which differ from those found in the domain literature. They also reta in a large number of symbolic abstractions for images. These abstractions (which we call visual chunks) play an important role in guiding the inference process and integrating collections of tacit knowledge of the geological experts. We infer from our experience that the knowledge acquisition process in this domain should consider that inference and domain objects are parts of distinct ontologies. A special representation formalism, kgraphs+, is proposed as a tool to model the objects that support the infer ence and how they are related to the domain ontology.
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Abel, M., Mastella, L.S., Silva, L.A.L., Campbell, J.A., De Ros, L.F. (2004). How to Model Visual Knowledge: A Study of Expertise in Oil-Reservoir Evaluation. In: Galindo, F., Takizawa, M., Traunmüller, R. (eds) Database and Expert Systems Applications. DEXA 2004. Lecture Notes in Computer Science, vol 3180. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30075-5_44
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DOI: https://doi.org/10.1007/978-3-540-30075-5_44
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