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Data integration in microbial genomics ... - Jacobs University

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1.1. From data to knowledge 3<br />

Figure 1.2: Exchange rate example, modified from: [Krcmar, 2009]<br />

still no consensus on the nature of knowledge among <strong>in</strong>formation scientists<br />

[Rowley, 2007].<br />

For this work, knowledge is def<strong>in</strong>ed as condensed<br />

<strong>in</strong>formation that can be obta<strong>in</strong>ed through empirical and thorough<br />

analysis of data and <strong>in</strong>formation by apply<strong>in</strong>g reproducible methods<br />

2 . Furthermore, knowledge aids decision mak<strong>in</strong>g. One aspect of<br />

knowledge is that it is always bound to the <strong>in</strong>dividual and has to be<br />

learned. Once learned, knowledge becomes a part of the m<strong>in</strong>d and is<br />

then called tacit or implicit knowledge. In contrast, explicit knowledge<br />

has been recorded <strong>in</strong> some form that allows an <strong>in</strong>dividual to transform<br />

this explicit knowledge <strong>in</strong>to tacit knowledge aga<strong>in</strong> [P. Bocij and<br />

Hickie, 2005]. Science ma<strong>in</strong>ly focuses on explicit knowledge that can<br />

be empirically derived and reproduced <strong>in</strong> experiments and recorded <strong>in</strong><br />

publications, books or databases.<br />

In computer science, knowledge can be computed. When a real world<br />

doma<strong>in</strong> has been mapped onto a computable formalism, knowledge can<br />

be derived from it. Computable formalisms are for example First Order<br />

Logic (FOL) or ontologies. FOL is a formal logical system which<br />

consists of a formal language and a set of <strong>in</strong>ference rules that are<br />

2 This def<strong>in</strong>ition is consistent with the def<strong>in</strong>ition of knowledge that is obta<strong>in</strong>ed by the application<br />

of scientific methods [Wilson, 1991].

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