@inbook{f6012779c01b47fb94d72fb57835fd73,
title = "How to model visual knowledge: A study of expertise in oil-reservoir evaluation",
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 images 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 retain 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 inference and how they are related to the domain ontology.",
keywords = "Expertise, Knowledge acquisition, Knowledge representation, Petroleum exploration, Visual knowledge",
author = "Mara Abel and Mastella, {Laura S.} and {Lima Silva}, {Lu{\'i}s A.} and Campbell, {John A.} and {De Ros}, {Luis Fernando}",
year = "2004",
doi = "10.1007/978-3-540-30075-5_44",
language = "English",
isbn = "3540229361",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "455--464",
editor = "Fernando Galindo and Makoto Takizawa and Roland Traunmuller",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
address = "Germany",
}