Knowledge Discovery, Knowledge Engineering and Knowledge by Joydeep Ghosh, Aayush Sharma (auth.), Ana Fred, Jan L. G.

By Joydeep Ghosh, Aayush Sharma (auth.), Ana Fred, Jan L. G. Dietz, Kecheng Liu, Joaquim Filipe (eds.)

This ebook constitutes the completely refereed post-conference court cases of the second one foreign Joint convention on wisdom Discovery, wisdom Engineering, and data administration, IC3K 2010, held in Valencia, Spain, in October 2010. This ebook contains revised and prolonged models of a strict collection of the easiest papers offered on the convention; 26 revised complete papers including 2 invited lectures have been rigorously reviewed and chosen from 369 submissions. in keeping with the 3 lined meetings KDIR 2010, KEOD 2010, and KMIS 2010, the papers are geared up in topical sections on wisdom discovery and data retrieval, wisdom engineering and ontology improvement, and on wisdom administration and data sharing.

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In addition to this, relating the concept to its context is equally as important as defining it intrinsically, and conventional methods often fail exactly at satisfying this requirement. The contribution of this work is twofold however, on the one hand fixing the semantics of the concept in a conceptual model while on the second hand enforcing the use of conceptual models in the bioinformatics domain. Bioinformatics has seen a rapid evolution in the past decade, starting with the sequencing of the human genome in 2000 by Venter and Collins [14], and the amount of data being generated is constantly growing.

By providing the SNP concept as an extension to the already existing conceptual model of the human genome [12] [13] both criteria at defining the concept are satisfied: rigorously describing what a SNP is, and relating it to its context. Explaining the various uses of the SNP concept, separating them into their appropriate conceptual context and presenting a conceptual modeling approach will allow solving this ambiguity. This is achieved by answering the main research question; What makes a genetic variation, classified as a SNP different from those genetic variations not classified as SNP?.

As a result of the ambiguity intrinsically associated to natural language, defining the concept exhaustively this way has proven to be a daunting task. In addition to this, relating the concept to its context is equally as important as defining it intrinsically, and conventional methods often fail exactly at satisfying this requirement. The contribution of this work is twofold however, on the one hand fixing the semantics of the concept in a conceptual model while on the second hand enforcing the use of conceptual models in the bioinformatics domain.

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