An Ontology Approach for Knowledge Acquisition and Development of Health Information System (HIS)

This paper emphasizes various knowledge acquisition approaches in terms of tacit and explicit knowledge management that can be helpful to capture, codify and communicate within medical unit. The semantic-based knowledge management system (SKMS) supports knowledge acquisition and incorporates various approaches to provide systematic practical platform to knowledge practitioners and to identify various roles of healthcare professionals, tasks that can be performed according to personnel’s competencies, and activities that are carried out as a part of tasks to achieve defined goals of clinical process. This research outcome gives new vision to IT practitioners to manage the tacit and implicit knowledge in XML format which can be taken as foundation for the development of information systems (IS) so that domain end-users can receive timely healthcare related services according to their demands and needs

Layers in the Fabric of Mind: A Critical Review of Cognitive Ontogeny

The essay is critically examines the conceptual problems with the influential modularity model of mind. We shall see that one of the essential characters of modules, namely informational encapsulation, is not only inessential, it ties a knot at a crucial place blocking the solution to the problem of understanding the formation of concepts from percepts (nodes of procedural knowledge). Subsequently I propose that concept formation takes place by modulation of modules leading to cross-representations, which were otherwise prevented by encapsulation. It must be noted that the argument is not against modular architecture, but a variety of an architecture that prevents interaction among modules. This is followed by a brief argument demonstrating that module without modularization, i.e. without developmental history, is impossible. Finally the emerging picture of cognitive development is drawn in the form of the layers in the fabric of mind, with a brief statement of the possible implications

Supporting organisational learning: an overview of the ENRICH approach

Traditional training separates learning from the work context in which the newly acquired knowledge is to be applied. This requires the worker themselves to apply imparted theoretical knowledge to knowledge in practice, a process that is grossly inefficient. The ENRICH approach builds on organisational learning theory to intertwine working and learning. The ENRICH methodology incorporates theories of learning at the individual, group and organisational level. Individual level learning is supported through the provision of semantically related resources to support problem reframing and to challenge assumptions. Group learning is supported through the evolution of domain concepts through work documents and representations linked to formal models of group knowledge, and the development of group practices and perspectives through enhanced sharing and collaboration. Organisational learning is supported through exposure to customs and conventions of other groups through shared best practices and knowledge models. The approach is being investigated in a range of industrial settings and applications

Knowledge formalization in experience feedback processes : an ontology-based approach

Because of the current trend of integration and interoperability of industrial systems, their size and complexity continue to grow making it more difficult to analyze, to understand and to solve the problems that happen in their organizations. Continuous improvement methodologies are powerful tools in order to understand and to solve problems, to control the effects of changes and finally to capitalize knowledge about changes and improvements. These tools involve suitably represent knowledge relating to the concerned system. Consequently, knowledge management (KM) is an increasingly important source of competitive advantage for organizations. Particularly, the capitalization and sharing of knowledge resulting from experience feedback are elements which play an essential role in the continuous improvement of industrial activities. In this paper, the contribution deals with semantic interoperability and relates to the structuring and the formalization of an experience feedback (EF) process aiming at transforming information or understanding gained by experience into explicit knowledge. The reuse of such knowledge has proved to have significant impact on achieving themissions of companies. However, the means of describing the knowledge objects of an experience generally remain informal. Based on an experience feedback process model and conceptual graphs, this paper takes domain ontology as a framework for the clarification of explicit knowledge and know-how, the aim of which is to get lessons learned descriptions that are significant, correct and applicable

On the adequacy of current empirical evaluations of formal models of categorization

Categorization is one of the fundamental building blocks of cognition, and the study of categorization is notable for the extent to which formal modeling has been a central and influential component of research. However, the field has seen a proliferation of noncomplementary models with little consensus on the relative adequacy of these accounts. Progress in assessing the relative adequacy of formal categorization models has, to date, been limited because (a) formal model comparisons are narrow in the number of models and phenomena considered and (b) models do not often clearly define their explanatory scope. Progress is further hampered by the practice of fitting models with arbitrarily variable parameters to each data set independently. Reviewing examples of good practice in the literature, we conclude that model comparisons are most fruitful when relative adequacy is assessed by comparing well-defined models on the basis of the number and proportion of irreversible, ordinal, penetrable successes (principles of minimal flexibility, breadth, good-enough precision, maximal simplicity, and psychological focus)