Knowledge Management Support System Research Articles

Ontology Creation Process in Knowledge Management Support System for a Research Institute

Though the issue of knowledge management is a hot subject of interest in nowadays market companies, integrated solutions fit to the specific needs of research institutes still require more attention. This paper documents a part of the research activities performed at National Institute of Telecommunications, related to development of research institute knowledge management support system. The ideas lying in the background of the system come from the recent theories of knowledge creation and creativity support and from experience with everyday practice of knowledge management in market companies. Main focus is put here on the issue of creation of a research topics ontology that is meant to be a semantic backbone of the system. Three-stage approach is proposed, aiming at the construction of ontologies for different levels of organizational hierarchy, from individual researcher, through group or unit, up to the whole institute. Created ontologies are linked to knowledge resources and support diverse activities performed at those levels

A Digital Platform to Facilitate the Resilience of Rural Territories

This work shows how we have designed and implemented a digital platform for Smart Villages, which can serve as a knowledge management and decision support system for rural stakeholders, including planners, administrative staff, and decision-makers. Our platform is intended to help pilot a smooth transition into a sustainable administration, help to boost rural services through digital innovation, and, in general, reduce the gap concerning the city’s world. Although the platform has arisen around a community belonging to the European Alpine Space, the lessons learned can be easily transferred to other scenarios in which determining and improving the degree of smartness maturity of the rural communities is a critical challenge that can facilitate undertaking public or private investments. Our goal is to provide the necessary tools for collaboration and sharing experiences and data collection and analysis to enable the best possible informed decision-making concerning the promotion of smarter villages.

Combining familial hypercholesterolemia and statin genetic studies as a strategy for the implementation of pharmacogenomics. A multidisciplinary approach.

The diagnostic process of familial hypercholesterolemia frequently involves the use of genetic studies. Patients are treated with lipid-lowering drugs, frequently statins. Although pharmacogenomic clinical practice guidelines focusing on genotype-based statin prescription have been published, their use in routine clinical practice remains very modest.We have implemented a new NGS strategy that combines a panel of genes related to familial hypercholesterolemia with genomic regions related to the pharmacogenomics of lipid-lowering drugs described in clinical practice guidelines and in EMA and FDA drug labels. A multidisciplinary team of doctors, biologists, and pharmacists creates a clinical report that provides diagnostic and therapeutic findings using a knowledge management and clinical decision support system, as well as an algorithm for treatment selection.For 12 months, a total of 483 genetic diagnostic studies for familial hypercholesterolemia were carried out, of which 221 (45.8%) requested a complementary pharmacogenomic test. Of these 221 patients, 66.5% were carriers of actionable variants in any of the studied pharmacogenomic pathways: 46.6% of patients in one pathway, 19.0% in two pathways, and 0.9% in three pathways. 45.7% of patients could have a response to atorvastatin different from that of the reference population, 45.7% for simvastatin and lovastatin, 29.0% for fluvastatin, and 6.7% patients for pitavastatin.This implementation approach facilitates the incorporation of pharmacogenomic studies in clinical care practice, it does not add complexity nor additional steps to laboratory processes, and improves the pharmacotherapeutic process of patients.

An ontology-based knowledge management approach supporting simulation-aided design for car crash simulation in the development phase

In the automotive industry, the design process is both costly and time-consuming. This research focuses on improving the design process by mainly reducing time while producing more robust vehicles. Vehicle development is based on simulation; thus, the design process is referred to as simulation-aided design. Engineering design is highly collaborative and knowledge intensive. Therefore, knowledge management plays a crucial role in today's global economy and is essential for the competitiveness of companies. However, current research on engineering knowledge management focuses on either the codification or the personalisation approaches of knowledge management. Thus, this paper addresses an integrated and collaborative approach. This paper aims to develop an ontology-based knowledge management approach to support simulation-aided design, specifically car crash simulation. The knowledge management support system is designed to ensure the capture and retrieval of engineering knowledge and to enable collaboration between different stakeholders. An evaluation of the models and technologies used is also undertaken, based on use case scenarios.

Intellectual Capital and Operational Excellence: An Influential Assessment

Competent intellectual capital is one of the most essential wealth that an organization requires in the present era of cutthroat competition. Operations management is nothing but management of operational processes in every big and small organization, and such activities constitute a major chunk of all organizational activities. Therefore, the present work targets to explore the association between intellectual capital and operational excellence, review of already conducted studies in the said area, and future directions through systematic literature review process. A total number of 165 articles provided by Scopus database (2010 to 2019) is used for analysis and interpretation. Bibliometric analysis and network analysis deliver significant clusters (operations management and optimization; intellectual capital and intellectual investment; knowledge management and decision support system; strategic planning and resource allocation; sustainable operations management and performance standards; behavioural research and change management), which is in turn a novel contribution of this article. The study concludes with a proposed conceptual model and key take away for researchers, academicians, and managers.

Feature assessment and ranking for classification with nonlinear sparse representation and approximate dependence analysis

Feature selection has received significant attention in knowledge management and decision support systems in the past decades. In this study, kernel-based sparse representation and feature dependence analysis are integrated into a feature assessment and ranking framework. The proposed method utilizes the advantages of the kernel-based sparse representation technique and of the information theoretic metric to iteratively obtain the salient feature cluster. Then, a novel approximate dependence analysis is applied to further maintain complementarity while eliminating redundancy among the features selected by nonlinear orthogonal matching pursuit (NOMP). This can effectively prevent the significant bias caused by the pairwise correlation analysis for a large-scale feature set. To illustrate the effectiveness of the proposed method, classification experiments are conducted with three representative classifiers, on nine well-known datasets. The experimental results show the superiority of the proposed method compared with the representative information theoretic and model-based methods in classification for data-driven decision support systems.

Modeling Sequential Information Acquisition Behavior in Rational Decision Making

ABSTRACTMost real‐life decisions are made with less than perfect information and there is often some opportunity to acquire additional information to increase the quality of the decision. In this article, we define and study the sequential information acquisition process of a rational decision maker (DM) when allowed to acquire any finite amount of information from a set of products defined by vectors of characteristics. The information acquisition process of the DM depends both on the values of the characteristics observed previously and the number and potential realizations of the remaining characteristics. Each time an observation is acquired, the DM modifies the probability of improving upon the products already observed with the number of observations available. We construct two real‐valued functions whose crossing points determine the decision of how to allocate each available piece of information. We provide several numerical simulations to illustrate the information acquisition incentives defining the behavior of the DM. Applications to knowledge management and decision support systems follow immediately from our results, particularly when considering the introduction and acceptance of new technological products and when formalizing online search environments.

Performance Evaluation of South Esk Hydrological Sensor Web: Unsupervised Machine Learning and Semantic Linked Data Approach

Technological progress has lead the sensor network domain to an era where environmental and agricultural domain applications are completely dependent on hydrological sensor networks. Data from the sensor networks are being used for knowledge management and critical decision support system. The quality of data can, however, vary widely. Existing automated quality assurance approach based on simple threshold rulebase could potentially miss serious errors requiring robust and complex domain knowledge to identify. This paper proposes a linked data concept, unsupervised pattern recognition, and semantic ontologies based dynamic framework to assess the reliability of hydrological sensor network and evaluate the performance of the sensor network. Newly designed framework is used successfully to evaluate the South Esk hydrological sensor web in Tasmania, indicating that domain ontology based linked data approach could be a very useful methodology for quality assurance of the complex data.

Developing a Framework for Integrating Knowledge Management and Decision Support Systems: Application to Time Series Forecasting

Developing a Framework for Integrating Knowledge Management and Decision Support Systems: Application to Time Series Forecasting

The Combination of Knowledge Management and Data mining with Knowledge Warehouse

Effective knowledge management (KM) enhances products, improves operational efficiency, speeds deployment, increases sales and profits, and creates customer satisfaction. Data warehousing provides an infrastructure that enables business to extract, and store vast amounts of corporate data. The purpose of data warehouse is to empower the knowledge workers with information that allows them to make decision based on a foundation of fact. The aim of this paper is to integrate a framework of knowledge management and data mining with knowledge warehouse. Therefore, first, it will brief review the existing of knowledge management, data mining, and decision support system. We then present on knowledge management or supplementary relationship between the knowledge management, data mining and decision support system with knowledge warehouse. Second, knowledge, knowledge management and knowledge process is defined. Third, we introduce decision support, data mining and data warehouse support of knowledge management, and point out data mining in data warehouse environment. Four, the warehouse is defined. Using this definition, it can drive framework of knowledge warehouse. This framework contain 6 layers: knowledge input, knowledge activity, data store, application server, application system data base, and user client. In this paper some suggestions are made to get knowledge with data mining, which will provide the decision maker with an intelligent platform that enhances all phase of knowledge management and knowledge process.

A mobile knowledge management and decision support tool for soil analysis

This paper describes the implementation and evaluation of a mobile knowledge management and decision support system to assist archaeologists in dealing with soils. Our view is that provision of a mobile tool which provides access to expert knowledge and a means of recording pertinent onsite information will be of great benefit in ensuring crucial information about an excavation is not lost and that the excavation proceeds in an appropriate manner. In this paper we discuss the tool developed, and detail how it has been evaluated via a variety of workshop sessions with likely users, and discussions with advisory groups.

Designing CSCW system for integrated, web-based, cotton cultivation services

Computer Supported Collaborative Work (CSCW) systems have attracted the attention of many software implementers on the area of multimedia applications, however very few of them have been used in agriculture. The necessity for using the CSCW environment in agriculture arises from the utilization and the rapid development of modern strategies of plant cultivation. In this paper we present the design of an agricultural CSCW system, which aims to provide integrated, web-based, services for cotton cultivation. Designing and developing such a system is a complex task that requires dealing with a great number of challenges. We focused on a number of important interrelated issues of user profiles, providing an overview and an insight on the way we address them. The proposed framework is intended to contribute to a unified view of requirements of a knowledge management support system by identifying core components and functionalities.

EXPERT AND KNOWLEDGE SYSTEMS AND DATABASES OF THE BEST PRACTICE

Investigations on the similarities and differences of expert, knowledge management and decision support systems are presented in the paper. Explicit and tacit knowledge is analysed. The benefit of knowledge management systems, their development and implementation are analysed. The aspects of the best practice and its knowledge bases and databases are described. Practical possibilities to apply the knowledge systems are presented. On the base of practice acquired during the FP 6 project INTELCITIES the database of the best practice and the web‐based decision support system for real estate are developed. On the base of the BPJTA in PuBs project the database of the best practice and the web‐based decision support system for retrofit of public buildings are developed.

Knowledge management support for teachers

Business organizations worldwide are implementing techniques and technologies to better manage their knowledge. Their objective is to improve the quality of the contributions people make to their organizations by helping them to make sense of the context within which the organization exists; to take responsibility, cooperate, and share what they know and learn; and to effectively challenge, negotiate, and learn from others. We consider how the concepts, tools, and techniques of organizational knowledge management can be applied to the professional practices and development of teachers. We describe a framework for knowledge management support for teachers where the sharing of concrete knowledge scaffolds the attainment of more abstract levels of knowledge sharing. We describe the development of a knowledge management support system emphasizing long-term participatory design relationships between technologists and teachers, regional cooperation among teachers in adjacent school divisions, the integration of communication and practice, synchronous and asynchronous interactions, and multiple metaphors for organizing knowledge resources and activities.

A knowledge management reference model

A three‐layer, cognitive domains, functional and resources, reference model for knowledge management systems is developed. This model aims at providing the basis for identifying the processes to be supported by any knowledge management support system (KMSS), for modeling the dynamics of these processes, for developing a framework of a business‐aware approach to KMSS development methodology, and for developing blueprints for information/communication technology (ICT)‐based KMSS. The first layer deals with the organizational knowledge and its characterization in terms of knowledge things. The concept of “K‐manipulating situation” is introduced and used as a conceptual construct for structuring the functional aspects of KMSS. While this construct combines knowledge and its manipulating processes, it also captures the social aspects of them by including the involved actors and their roles. Examples from Matsushita’s “Home Bakery” case study are used to illustrate the application of the reference model.

Towards knowledge-based systems in clinical practice:: Development of an integrated clinical information and knowledge management support system

Given that clinicians presented with identical clinical information will act in different ways, there is a need to introduce into routine clinical practice methods and tools to support the scientific homogeneity and accountability of healthcare decisions and actions. The benefits expected from such action include an overall reduction in cost, improved quality of care, patient and public opinion satisfaction. Computer-based medical data processing has yielded methods and tools for managing the task away from the hospital management level and closer to the desired disease and patient management level. To this end, advanced applications of information and disease process modelling technologies have already demonstrated an ability to significantly augment clinical decision making as a by-product. The wide-spread acceptance of evidence-based medicine as the basis of cost-conscious and concurrently quality-wise accountable clinical practice suffices as evidence supporting this claim. Electronic libraries are one-step towards an online status of this key health-care delivery quality control environment. Nonetheless, to date, the underlying information and knowledge management technologies have failed to be integrated into any form of pragmatic or marketable online and real-time clinical decision making tool. One of the main obstacles that needs to be overcome is the development of systems that treat both information and knowledge as clinical objects with same modelling requirements. This paper describes the development of such a system in the form of an intelligent clinical information management system: a system which at the most fundamental level of clinical decision support facilitates both the organised acquisition of clinical information and knowledge and provides a test-bed for the development and evaluation of knowledge-based decision support functions.

Human capital knowledge value added

Knowledge value added is a new cost accounting technique making waves in intangibles accounting. It helps managers conduct a business process audit. However, the managers need a behavioral tool to understand the factors that influence human capital knowledge value add, in order to increase the organizational value add. This tool helps understand the knowledge professional’s perceptions of the organization’s culture towards intellectual enterprise, knowledge management support systems and processes, as well as individual value add, the perceived performance, innovation and consequences of quitting. The tool thus helps formulation of strategies towards effective management of human capital and creating higher value add. A leading Indian infotech organization was studied as a case in point and the results are being used to design more effective knowledge management strategies.