Data integration in microbial genomics ... - Jacobs University

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2 1. Introduction syntax: data level more signs user sign subject semiotics meaning pragmatics: information level semantics Figure 1.1: data and information, modified from: [Berthel, 1975] bined to form expressions, which are called data. Rules that describe how these signs are validly combined are called syntax. Valid data expressions can often be combined to form even larger expressions. Whereas alphabets have a finite size, data expressions can in theory be infinite 1 . On the level of semantics, these data expressions become meaningful. When data are interpreted in their context by a user, they become information. Information can be defined as interpreted data. To transform data into information, it must be clear, to which subject these data are related to and in which context they were created. context-based [Rowley, 2007]. Thus, information is always subject-related and Information help to answer questions like “Who...?”, “How much ...?”, “How many ...?”, “ What ...?”, “ Where ...?” and “When ...?” [Ackoff, 1989]. Figure 1.2 shows an example. On the lowest level is an expression that consists of signs that are combined according to a syntax. The data expression alone is not meaningful, until this data is correctly interpreted to be an exchange rate. Once interpreted, the data expression becomes information. Whereas data and information can be clearly distinguished, it is somewhat harder to differentiate information and knowledge. There is 1 In reality data has to be stored on a physical medium such as a harddrive and therefore can not be infinite in size [Beynon-Davies, 2002].
1.1. From data to knowledge 3 Figure 1.2: Exchange rate example, modified from: [Krcmar, 2009] still no consensus on the nature of knowledge among information scientists [Rowley, 2007]. For this work, knowledge is defined as condensed information that can be obtained through empirical and thorough analysis of data and information by applying reproducible methods 2 . Furthermore, knowledge aids decision making. One aspect of knowledge is that it is always bound to the individual and has to be learned. Once learned, knowledge becomes a part of the mind and is then called tacit or implicit knowledge. In contrast, explicit knowledge has been recorded in some form that allows an individual to transform this explicit knowledge into tacit knowledge again [P. Bocij and Hickie, 2005]. Science mainly focuses on explicit knowledge that can be empirically derived and reproduced in experiments and recorded in publications, books or databases. In computer science, knowledge can be computed. When a real world domain has been mapped onto a computable formalism, knowledge can be derived from it. Computable formalisms are for example First Order Logic (FOL) or ontologies. FOL is a formal logical system which consists of a formal language and a set of inference rules that are 2 This definition is consistent with the definition of knowledge that is obtained by the application of scientific methods [Wilson, 1991].
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CHAPTER 4 MIMARKS The Minimum infor
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4.2. Introduction 57 edge generatio
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4.3. Development of MIMARKS 59 in t
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4.4. Survey of published parameters
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4.5. The MIMARKS checklist 63 Resul
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CHAPTER 5 MEGX.NET Integrated datab
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5.3. New database structure and con
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5.5. Summary 77 access charge: Max
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CHAPTER 7 SUMMARY AND DISCUSSION Th
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7.2. GSC standards development 89 T
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98 8. Conclusion and outlook nities
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100 8. Conclusion and outlook plina
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102 BIBLIOGRAPHY [Beynon-Davies, 20
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104 BIBLIOGRAPHY oceanic regions by
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106 BIBLIOGRAPHY [Giovannoni et al.
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108 BIBLIOGRAPHY [Kitano, 2002] Kit
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110 BIBLIOGRAPHY pathways in marine
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112 BIBLIOGRAPHY [Ramette, 2007] Ra
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114 BIBLIOGRAPHY (2006). Microbial
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116 BIBLIOGRAPHY [Williamson et al.
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CHAPTER 9 ACKNOWLEDGEMENTS First, I
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