Comparative analysis of knowledge representation and reasoning requirements across a range of life sciences textbooks

Journal of Biomedical Semantics
Vinay K ChaudhriNeil Yorke-Smith

Abstract

Using knowledge representation for biomedical projects is now commonplace. In previous work, we represented the knowledge found in a college-level biology textbook in a fashion useful for answering questions. We showed that embedding the knowledge representation and question-answering abilities in an electronic textbook helped to engage student interest and improve learning. A natural question that arises from this success, and this paper's primary focus, is whether a similar approach is applicable across a range of life science textbooks. To answer that question, we considered four different textbooks, ranging from a below-introductory college biology text to an advanced, graduate-level neuroscience textbook. For these textbooks, we investigated the following questions: (1) To what extent is knowledge shared between the different textbooks? (2) To what extent can the same upper ontology be used to represent the knowledge found in different textbooks? (3) To what extent can the questions of interest for a range of textbooks be answered by using the same reasoning mechanisms? Our existing modeling and reasoning methods apply especially well both to a textbook that is comparable in level to the text studied in our previous work (...Continue Reading

References

May 17, 2005·Genome Biology·Barry SmithCornelius Rosse
Aug 15, 2009·Science·Allen H Renear, Carole L Palmer
Dec 10, 2013·Nucleic Acids Research·Xosé M Fernández-SuárezMichael Y Galperin

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Methods Mentioned

BETA
or
transmission electron microscopy

Software Mentioned

BioPortal
AURA
Webb
Kandel
Web Ontology Language
Digital Aristotle
AURA Library
Inquire
CLIB

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