174 research outputs found

    KNOWLEDGE MANAGEMENT IN HIGHER EDUCATION – AN ONTOLOGICAL APPROACH IN COLLABORATIVE ENVIRONMENTS

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    The paper presents an ontology-based knowledge management system developed for a Romanian university. The university used a classic Management Information System (MIS), which was the starting point for developing the knowledge management system. The developed knowledge management system has a general ontology, containing terms which are valid for a public institution, and specific ontology for two process categories, didactic and research process. The ontology is implemented using Protege. The results are very encouraging and suggest several future developments.business intelligence, knowledge management, ontology, university

    Special Theme of Research in Information Systems Analysis and Design - I. Unraveling Knowledge Requirements Through Business Process Analysis

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    Organizations analyze their business processes in order to improve them. Business processes are also considered retainers, users and creators of organizational knowledge. Thus, they can be analyzed to identify the knowledge used, created and embedded in them. A process analysis approach that focuses on redesign does not necessarily capture the knowledge used and created in a process. Choosing a knowledge-focused approach should lead to understanding knowledge needs but might not lead to improved business processes. This paper describes an approach for Knowledge Requirements Analysis (KRA) that combines process analysis with identifying knowledge used and created during the process. KRA is the process of identifying and analyzing existing organizational knowledge and prescribing improvements to it. The KRA methodology presented in this paper combines two methods: a knowledge engineering method (CommonKADS) and a process modeling method (EDPDT). The EDPDT constructs are used to operationalize the organization and task models of CommonKADS and thus create the KRA methodology. The methodology was applied successfully to the process of ethical reviews of grant applications in a university. The main advantage of the proposed methodology is that it enables organizations to keep track of their knowledge resources embedded in various business processes. Knowledge that is not shared or used can be detected and new knowledge can be identified to support and improve existing processes better. This approach can lead to improved knowledge management in organization

    Building an ontological knowledgebase for bridge maintenance

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    The operation stage has the biggest potential value in the bridge life cycle management, and it often critically influences the overall cost of the bridge. As such, changes in the efficiency of the project's operation stage could be of significant benefit to the overall project. However, current approaches in the operation stage often lack the effective support of computer-aided tools. This research presents a holistic method based on an ontology to achieve automatic rule checking and improve the management and communication of knowledge related to bridge maintenance. The developed ontology can also facilitate a smarter decision-making process for bridge management by informing engineers of choices with different considerations. Three approaches; semantic validation, syntactical validation, and case study validation, have been adopted to evaluate this ontology and demonstrate how the developed ontology can be used by engineers when dealing with different issues. The results showed that this approach can create a holistic knowledge base that can integrate various domain knowledge to enable bridge engineers to make more comprehensive decisions rather than a single objective-targeted delivery

    A Structure of Problem Solving Methods for Real Time Decision Support in Traffic Control

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    This article describes a knowledge-based application in the domain of road traffic management that we have developed following a knowledge modeling approach and the notion of problem-solving method. The article presents first a domain-independent model for real-time decision support as a structured collection of problem solving methods. Then, it is described how this general model is used to develop an operational version for the domain of traffic management. For this purpose, a particular knowledge modeling tool, called KSM (Knowledge Structure Manager), was applied. Finally, the article shows an application developed for a traffic network of the city of Madrid and it is compared with a second application developed for a different traffic area of the city of Barcelona

    Clinical Guideline Audit and Knowledge Elicitation Using the MDS Tool and Techniques

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    This paper outlines a study, utilising the MDS methodology and tool to create a knowledge model based on clinical experts’ interpreted knowledge of clinical guidelines. The study demonstrated the elicitation of tacit expert knowledge when the formalised processes of the MDS were applied to model a clinical expert’s interpretation of the knowledge content of a clinical guideline onto the specialised MDS architecture

    Design methodology for ontology-based multi-agent applications (MOMA)

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    Software agents and multi-agent systems (MAS) have grown into a very active area of research and commercial development activity. There are many current emerging real-world applications spanning multitude of diverse domains. In the context of agents, ontology has been widely recognised for their significant benefits to interoperability, reusability, and both development and operational aspects of agent systems and applications. Ontology-based multi-agent systems (OBMAS) exploit these advantages in providing intelligent and semantically aware applications. In addressing the lack of support for ontology in existing methodologies for multi-agent development, this thesis proposes a design methodology for the building of such intelligent multi-agent applications called MOMA. This alternative approach focuses on the development of ontology as the driving force of the development process. By allowing the domain and characteristics of utilisation and experimentation to be dictated through ontology, researchers and domain experts can specify the agent application without any knowledge of agent design and lower level programming. Through the use of a structured ontology model and the use of integrated tools, this approach contributes towards the building of semantically aware intelligent applications for use by researchers and domain experts. MOMA is evaluated through case studies in two different domains: financial services and e-Health

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

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    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

    An ontology framework for developing platform-independent knowledge-based engineering systems in the aerospace industry

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    This paper presents the development of a novel knowledge-based engineering (KBE) framework for implementing platform-independent knowledge-enabled product design systems within the aerospace industry. The aim of the KBE framework is to strengthen the structure, reuse and portability of knowledge consumed within KBE systems in view of supporting the cost-effective and long-term preservation of knowledge within such systems. The proposed KBE framework uses an ontology-based approach for semantic knowledge management and adopts a model-driven architecture style from the software engineering discipline. Its phases are mainly (1) Capture knowledge required for KBE system; (2) Ontology model construct of KBE system; (3) Platform-independent model (PIM) technology selection and implementation and (4) Integration of PIM KBE knowledge with computer-aided design system. A rigorous methodology is employed which is comprised of five qualitative phases namely, requirement analysis for the KBE framework, identifying software and ontological engineering elements, integration of both elements, proof of concept prototype demonstrator and finally experts validation. A case study investigating four primitive three-dimensional geometry shapes is used to quantify the applicability of the KBE framework in the aerospace industry. Additionally, experts within the aerospace and software engineering sector validated the strengths/benefits and limitations of the KBE framework. The major benefits of the developed approach are in the reduction of man-hours required for developing KBE systems within the aerospace industry and the maintainability and abstraction of the knowledge required for developing KBE systems. This approach strengthens knowledge reuse and eliminates platform-specific approaches to developing KBE systems ensuring the preservation of KBE knowledge for the long term

    Capture and Maintenance of Constraints in Engineering Design

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    The thesis investigates two domains, initially the kite domain and then part of a more demanding Rolls-Royce domain (jet engine design). Four main types of refinement rules that use the associated application conditions and domain ontology to support the maintenance of constraints are proposed. The refinement rules have been implemented in ConEditor and the extended system is known as ConEditor+. With the help of ConEditor+, the thesis demonstrates that an explicit representation of application conditions together with the corresponding constraints and the domain ontology can be used to detect inconsistencies, redundancy, subsumption and fusion, reduce the number of spurious inconsistencies and prevent the identification of inappropriate refinements of redundancy, subsumption and fusion between pairs of constraints.EThOS - Electronic Theses Online ServiceGBUnited Kingdo
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