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Analyse und Bewertung der Modellgüte in Hybrid Wikis

Last modified Dec 3, 2013

Abstract

Information is crucial for many enterprises and so is its management. Although information management (IM) is quite well understood by research, practitioners do not have holistic, easy to use tools to support IM. To date, different kinds of wiki systems promise to fulfill such requirements for a sophisticated IM. One special kind of wiki system are Hybrid Wikis, because they try to exploit the benefits of standard as well as semantic wikis. Up to this point, the Hybrid Wiki concepts for structuring information have not been tested in detail and therefore there is no proof of their feasibility. To supply such evidence, the structure of information entered in Hybrid Wikis by non expert users has to be at least as good as the structure of information models created by experienced users. For that reason, two challenges need to be met. First, criteria for well-structured information need to be acquired and decomposed into measurable metrics. Second, the structure of real HybridWikis has to be compared to the structure of other information models. This thesis describes a laboratory experiment conducted
with eleven students in which Hybrid Wiki models were compared to Unified Modeling Language (UML) models. The different models created during the experiment are analyzed according to their structural complexity, semantic quality in terms of completeness and validity, and their perceived semantic quality. The results indicate that models extracted from Hybrid Wikis have a significantly better validity compared to UML models and that they are not worse in the other quality factors. With these results, a next step towards an evidence for high quality information structure within HybridWikis has been taken.

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