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Abstract-Considering different aspects of knowledge functioning, context is poorly understood in spite of intuitively identifying this concept with environmental recognition. For dynamic knowledge, context especially seems to be an essential factor of change. Investigation on the impact of context on knowledge dynamics or more generally on the relationship between knowledge and its contextual interpretation is important in order to understand knowledge dynamics. The aim of this paper is to research and examine the nature of knowledge transformation (a specific sort of life-cycle), and to identify contextual factors affecting knowledge dynamics.

Nowadays, we face a huge amount of data and information sharing on the Web by different users worldwide. A multidimensional perspective in describing a university ontology seems to be very important for the modelling of higher education resources. This paper proposes a multi-dimensional knowledge model, designed to distribute and manage knowledge resources efficiently. We propose our model as the foundation of an advanced knowledge platform including the following dimensions: time, area and social. Three crucial domains should be considered in this model: educational, research and managerial. The ontology including the mentioned knowledge management aspects is prepared using Ontorion Fluent Editor.

Observing new concepts in information technology, we pay attention to its impact on more effective supporting human and organisational knowledge. Knowledge management (KM) is one of such promising and intriguing concepts. Its goals and infrastructures are defined in different ways, therefore interdisciplinary approach seems to be useful. We have presented a short survey of theoretical concepts in management, marketing and decision theory, which were adapted by the theory of KM. On the other hand, knowledge validation (KV), defined as two procedures: verification and evaluation any form of knowledge, is aimed on assuring its quality. The paper discusses the crucial interrelationships between knowledge validation and management. The main goal of this work is positioning KV activities in the context of knowledge management process, emphasising usability of KV techniques during the whole process.

Knowledge-Based (KB) technology is being applied to complex problem solving and safety and business critical tasks in many application domains. Concerns have naturally arisen as to the dependability of Knowledge-Based Systems (KBS). As with any software, attention to quality and safety must be paid throughout development of a KBS, and rigorous Verification and Validation (V&V) techniques must be employed. Research in V&V of KBSs has emerged as a distinct field only in the last decade, and is intended to address issues associated with quality and safety aspects of KBSs, and to provide such applications with the same degree of dependability as conventional applications. In recent years, V&V of KBSs has been the topic of annual workshops associated with the main AI conferences, such as AAAI, IJCAI and ECAI.

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Abstract. Knowledge granularity, usually identified with the size of knowledge granules, seems to be real challenge for knowledge consumers as well as for knowledge creators. In this paper, relationships between knowledge granularity as a result of different ways of a knowledge representation are considered. The paper deals with the problem of developing knowledge grid in the context of encapsulation of knowledge including different dimensions and measures. The origin of the problem is discussed in the first section stressing flexibility of knowledge interpretations. Concepts of knowledge granularity (also from formal point of view) are presented in the next section. The nature of well represented knowledge is considered in the next chapter with references to granularity of knowledge. In the last part of the paper the question of formulating knowledge granularity in the context of knowledge grid concepts is discussed. This document comprising guidelines for authors is divided into several sections.

Knowledge granularity is often regarded as one of the essential factors of knowledge repositories basically in terms of ways of knowledge gathering and storing as well as its usability. The aim of this paper is to discuss the importance of this phenomena in the case of contextual classification. This kind of directed granulation by context gives possibility to generate new and intelligent knowledge structure, to see a problem through many context simultaneously perspectives or through one context perspective. A part of the investigation of usability of context-based approaches in creation knowledge structures interrelationships between knowledge granularity and effectiveness of classification tasks is discussed.