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Pyramid: Data – Information – Knowledge – Wisdom (DIKW)  

Pyramid: Data – Information – Knowledge – Wisdom (DIKW)  

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The mining methods are classified as the methods of data analysis and the knowledge acquisition and they are derived from the methods of “Knowledge Discovery”. Within the scope of these methods, there are two main variants associated with a form of data, i.e.: “data” and “text mining”. The author of the paper tries to find an answer to a question a...

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... Gajzler proposed a scheme to support the technological decisions through a text mining analysis, that is able to provide a quantitative representation of text documents to provide a tree diagram that shows that it is feasible to perform such analysis to result in an accurate statistical analysis. He also proposed another classification mechanism that is capable of measuring how the location affects the selection criteria of apartment sales [26]. Bilal and Oyedele developed a benchmarking system which is capable to evaluate the tender profitability using deep learning and text mining techniques combined with Big Data processing tools, the model generated a list of seventeen key performance indicators (KPIs) which wraps the different aspects related to each project that affect its profitability [27]. ...
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... Gajzler [42] shows a good and condensed view of the DIKW pyramid, which evolved over many years, as can be seen in figure 2.3. "The DIKW pyramid, also known variously as the DIKW hierarchy, wisdom hierarchy, knowledge hierarchy, information hierarchy, and the data pyramid, refers loosely to a class of models for representing purported structural and/or functional relationships between data, information, knowledge, and wisdom. ...
... DIKW pyramid by Gajzler[42]. ...
Thesis
Large and complex systems are used in every field of industry and research. Most of these systems can be classified as knowledge processing systems or subgroups of these. We investigate how someone can trust such systems and their outputs when only knowing how trustable the used inputs and sources are and how the system is working. After broad structured investigations the conclusion was that there exist some ways and methods in a larger context, but there is a strong need for embedding trust in particular into the work with knowledge processing systems, so the first contribution of this thesis is a sound and comparing literature review on knowledge processing and trust and their related research fields. One hurdle in this is also the multidisciplinary application of the term "Trust" and finding a distinguished handling and definition for applying trust in a technical domain. The second contribution of this thesis is the proposing of a definition of the "Trust Model" terminology in the context of knowledge processing and the investigation of suitable trust models. These models are the "Binary Trust Model", the "Probabilistic Trust Model", the "Opinion-Space Trust Model", and our self developed "Weighted Arithmetic Mean Trust Model" which suits in particular for the application in knowledge processing systems. Furthermore as a third contribution, we discuss these models for measurement, application, and ways of how to work with trust in knowledge processing systems. We focus on the possibilities of how to propagate trust through (multiple calculation steps executing) knowledge processing systems and evaluate and compare the investigated and developed trust models on several scenarios. We are convinced that the field of knowledge processing could highly benefit by using trust. With our research work and the evaluation of the models we are one step closer to our initial motivation of finding suitable ways for using trust in knowledge processing.
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In modern economic society, organizations’ competitiveness relies heavily on their ability to leverage and manage knowledge rather than in physical assets, some authors refer even though the concepts of knowledge management (KM) are being well implemented in the industrial sector, the construction segment, however, appears to have some difficulties in adopting the practices and strategies offered by KM. It is known that the construction sector (CS) is experiencing a time of instability and recession, and one of the causes of this may involve the lack of adaptation to knowledge era. Therefore, this paper, based on literature review, gives an overview of inhibitor and the facilitator factors of knowledge sharing (KS) with the objective to answer two questions: which of the KS inhibitors and facilitators characterize the CS? has the CS its specifics KS inhibitors and facilitators? It’s presented a framework in order to verify the existence of exclusive factors of the sector. At this point it is possible to suggest that CS has mainly organizational factors as inhibitors and the facilitator’s factors are almost individual. The facilitating factors might be the consequence of an effective and successful KS strategy and can be seen as guidelines to improve the construction industry organizational performance.
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Purpose Knowledge- and communication-intensive domains still long for a better support of creativity that considers legal requirements, compliance rules and administrative tasks as well, because current systems focus either on knowledge representation or business process management. The purpose of this paper is to discuss our model of integrated knowledge and business process representation and its presentation to users. Design/methodology/approach The authors follow a design science approach in the environment of patent prosecution, which is characterized by a highly standardized, legally prescribed process and individual knowledge study. Thus, the research is based on knowledge study, BPM, graph-based knowledge representation and user interface design. The authors iteratively designed and built a model and a prototype. To evaluate the approach, the authors used analytical proof of concept, real-world test scenarios and case studies in real-world settings, where the authors conducted observations and open interviews. Findings The authors designed a model and implemented a prototype for evolving and storing static and dynamic aspects of knowledge. The proposed solution leverages the flexibility of a graph-based model to enable open and not only continuously developing user-centered processes but also pre-defined ones. The authors further propose a user interface concept which supports users to benefit from the richness of the model but provides sufficient guidance. Originality/value The balanced integration of the data and task perspectives distinguishes the model significantly from other approaches such as BPM or knowledge graphs. The authors further provide a sophisticated user interface design, which allows the users to effectively and efficiently use the graph-based knowledge representation in their daily study.