Chapter 8. Global content management 123data + <strong>in</strong>terpretation = <strong>in</strong><strong>for</strong>mation + cognitive appropriation = knowledge + collectiverepresentation (<strong>in</strong> potentially multi-media and multi-modal <strong>for</strong>ms) <strong>for</strong> specificways of utilisation = contentEach higher level of complexity <strong>in</strong>tegrates diverse elements of the lower level. Usabilityaspects are most important on the content level. All lower levels rema<strong>in</strong>crucial on the higher levels, e.g., data management is still an important part ofcontent management.Look<strong>in</strong>g at the generic concept beh<strong>in</strong>d the word content, we would say: Contentis what is conta<strong>in</strong>ed <strong>in</strong> a written document or an electronic medium (or otherconta<strong>in</strong>ers of such types). We would expect that any content has been created byhumans with certa<strong>in</strong> <strong>in</strong>tentions, with goals or <strong>in</strong>terests <strong>in</strong> their m<strong>in</strong>ds. So we canconfirm that content is usually created <strong>for</strong> specific purposes (such as <strong>in</strong><strong>for</strong>mation,<strong>in</strong>struction, education, enterta<strong>in</strong>ment, arts, etc.).Content is often created <strong>in</strong> specific doma<strong>in</strong>s (arts, sciences, bus<strong>in</strong>ess/<strong>in</strong>dustry,government, social area, education, etc.). When specific content that was orig<strong>in</strong>allycreated <strong>in</strong> a science context, <strong>for</strong> <strong>in</strong>stance, it will have to be adapted andre-organised, <strong>in</strong> order to be able to re-use this content <strong>in</strong> other contexts, e.g., <strong>in</strong>secondary education or <strong>in</strong> <strong>in</strong>dustry.Discuss<strong>in</strong>g the term content, we cannot avoid deal<strong>in</strong>g with related terms suchas data, <strong>in</strong><strong>for</strong>mation, and knowledge. As we have seen above, it is essential tohave a clear dist<strong>in</strong>ction between the mean<strong>in</strong>gs of (the concepts beh<strong>in</strong>d) theseterms. From an economic or bus<strong>in</strong>ess perspective, ‘data is a set of particular andobjective facts about an event or simply the structured record of a transaction’(Tiwana 2000:59f.). We derive <strong>in</strong><strong>for</strong>mation by condens<strong>in</strong>g (summaris<strong>in</strong>g, elim<strong>in</strong>at<strong>in</strong>gnoise), calculat<strong>in</strong>g (analys<strong>in</strong>g), contextualis<strong>in</strong>g (relat<strong>in</strong>g data to concreteenvironments, add<strong>in</strong>g historical contexts), correct<strong>in</strong>g (revision of data collectionson the basis of experience) and categoris<strong>in</strong>g data (Davenport & Prusak 1998).Data management has always been a fundamental activity that is as importantas ever. Data repositories and data shar<strong>in</strong>g networks are the basic <strong>in</strong>frastructureabove the technical level <strong>in</strong> order to facilitate any activity on the levels above, i.e.,<strong>in</strong><strong>for</strong>mation management and knowledge management. The transition from <strong>in</strong><strong>for</strong>mationto knowledge can also be described from a systems theory po<strong>in</strong>t of view:a certa<strong>in</strong> level of activities has to be reached, so that knowledge ‘emerges’ from <strong>in</strong><strong>for</strong>mationflows. Many knowledge management specialists warn companies not toerroneously equate <strong>in</strong><strong>for</strong>mation flows to knowledge flows.In order to legitimately talk about knowledge, a number of conditions have tobe met:– Cognitive appropriation: knowledge is always the result of cognitive operations,of th<strong>in</strong>k<strong>in</strong>g processes. Yet knowledge is not limited to the personal,<strong>in</strong>dividual, subjective level. When people consciously share knowledge on the
124 Gerhard Bud<strong>in</strong>basis of directed communication processes, it is still knowledge, either referredto as collective or shared knowledge, or as <strong>in</strong>terpersonal, <strong>in</strong>ter-subjective, orobjective knowledge. In theories of scientific knowledge, the term ‘objectiveknowledge’ was ma<strong>in</strong>ly explicated by Popper (1972) and is the result of regulatedresearch processes such as hypothesis test<strong>in</strong>g, verification, proof, etc.,and that is written down <strong>in</strong> science communication processes. This is the justification<strong>for</strong> libraries to talk about their knowledge repositories <strong>in</strong> the <strong>for</strong>mof books that conta<strong>in</strong> this type of knowledge, i.e., objective knowledge. But asmentioned above, this knowledge is also subjective knowledge <strong>in</strong> researcherswhen they created it and when they communicate about it or when theydissem<strong>in</strong>ate it to others (e.g., <strong>in</strong> teach<strong>in</strong>g).– Complexity: the level of complexity is another factor <strong>in</strong> the transition from<strong>in</strong><strong>for</strong>mation to knowledge. The same processes as on the previous emergencelevel, from data to <strong>in</strong><strong>for</strong>mation, are relevant: condensation of <strong>in</strong><strong>for</strong>mation(summaris<strong>in</strong>g), analysis and <strong>in</strong>terpretation of <strong>in</strong><strong>for</strong>mation gathered, contextualisation(relat<strong>in</strong>g <strong>in</strong><strong>for</strong>mation to concrete problem solv<strong>in</strong>g situations, embedd<strong>in</strong>gand situat<strong>in</strong>g <strong>in</strong><strong>for</strong>mation <strong>in</strong> historical contexts and draw<strong>in</strong>g conclusionsfrom that, correct<strong>in</strong>g (revision of data collections on the basis ofexperience) and categoris<strong>in</strong>g knowledge accord<strong>in</strong>gly.– Life span: the validity of knowledge has to be checked all the time. Aga<strong>in</strong> we arerem<strong>in</strong>ded by Popper that all knowledge is unavoidably hypothetical <strong>in</strong> natureand that no knowledge is certa<strong>in</strong> <strong>for</strong> eternity. There<strong>for</strong>e we constantly have toredef<strong>in</strong>e the criteria by which we evaluate our current knowledge <strong>for</strong> its validity.Another metaphor from nuclear physics is used <strong>for</strong> knowledge, especially<strong>in</strong> scientometrics: the ‘half life’ of knowledge is constantly decreas<strong>in</strong>g, due tothe <strong>in</strong>crease <strong>in</strong> knowledge dynamics, not only <strong>in</strong> science and technology, also<strong>in</strong> <strong>in</strong>dustry, commerce and trade, even <strong>in</strong> culture, the arts, government andpublic sectors, the social sector, etc.In knowledge management, three basic steps <strong>in</strong> deal<strong>in</strong>g with knowledge are dist<strong>in</strong>guished(Nonaka & Takeuchi 1998; Tiwana 2000:71ff., etc.):– Knowledge acquisition: learn<strong>in</strong>g is the key <strong>for</strong> any knowledge managementactivity– Knowledge shar<strong>in</strong>g: the collaborative nature of knowledge is the focus– Knowledge utilisation: knowledge management systems have to allow also <strong>in</strong><strong>for</strong>malknowledge to be dealt with, not only <strong>for</strong>malised knowledge (this isa crucial factor <strong>in</strong> evaluat<strong>in</strong>g knowledge technologies <strong>for</strong> their suitability <strong>in</strong>knowledge management environments.The focus and the real goal of knowledge management are actually directed towardscontent, i.e., not on the <strong>for</strong>mal aspects of comput<strong>in</strong>g, but on what is beh<strong>in</strong>d
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27 Beylard-Ozeroff, Ann, Jana Král