2010The Knowledge Engineering ReviewRequires access

A survey of formalisms for representing and reasoning with scientific knowledge

Anthony Hunter, Weiru Liu

Open publisher page 18 citations

Abstract

Abstract With the rapid growth in the quantity and complexity of scientific knowledge available for scientists, and allied professionals, the problems associated with harnessing this knowledge are well recognized. Some of these problems are a result of the uncertainties and inconsistencies that arise in this knowledge. Other problems arise from heterogeneous and informal formats for this knowledge. To address these problems, developments in the application of knowledge representation and reasoning technologies can allow scientific knowledge to be captured in logic-based formalisms. Using such formalisms, we can undertake reasoning with the uncertainty and inconsistency to allow automated techniques to be used for querying and combining of scientific knowledge. Furthermore, by harnessing background knowledge, the querying and combining tasks can be carried out more intelligently. In this paper, we review some of the significant proposals for formalisms for representing and reasoning with scientific knowledge.

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What this paper is about

Abstract With the rapid growth in the quantity and complexity of scientific knowledge available for scientists, and allied professionals, the problems associated with harnessing this knowledge are well recognized. Some of these problems are a result of the uncertainties and inconsistencies that arise in this knowledge. Other problems arise from heterogeneous and informal formats for this knowledge. To address these problems, developments in the application of knowledge representation and reasoning technologies can allow scientific knowledge to be captured in logic-based formalisms. Using such formalisms, we can undertake reasoning with the uncertainty and inconsistency to allow automated techniques to be used for querying and combining of scientific knowledge. Furthermore, by harnessing background knowledge, the querying and combining tasks can be carried out more intelligently. In this paper, we review some of the significant proposals for formalisms for representing and reasoning with scientific knowledge.

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Available abstract

Abstract With the rapid growth in the quantity and complexity of scientific knowledge available for scientists, and allied professionals, the problems associated with harnessing this knowledge are well recognized. Some of these problems are a result of the uncertainties and inconsistencies that arise in this knowledge. Other problems arise from heterogeneous and informal formats for this knowledge. To address these problems, developments in the application of knowledge representation and reasoning technologies can allow scientific knowledge to be captured in logic-based formalisms. Using such formalisms, we can undertake reasoning with the uncertainty and inconsistency to allow automated techniques to be used for querying and combining of scientific knowledge. Furthermore, by harnessing background knowledge, the querying and combining tasks can be carried out more intelligently. In this paper, we review some of the significant proposals for formalisms for representing and reasoning with scientific knowledge.

Key concepts: Rotation formalisms in three dimensions, Computer science, Knowledge representation and reasoning, Scientific reasoning, Representation (politics), Data science, Sociology of scientific knowledge, Knowledge management

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