From the Publisher: "Towards the Semantic Web focuses on the application of Semantic Web technology and ontologies in particular to electronically available information to improve the quality of knowledge management in large and distributed organizations. Covering the key technologies for the next generation of the WWW, this book is a mixture of theory, tools and applications in an important area of WWW research." Aimed primarily at researchers and developers in the area of WWW-based knowledge management and information retrieval. It will also be a useful reference for students in computer science at the postgraduate level, academic and industrial researchers in the field, business managers who are aiming to increase the corporations' information infrastructure and industrial personnel who are tracking WWW technology developments in order to understand the business implications.
The information context of the modern organization is rapidly evolving in the face of intense global competition. Information technologies, including databases, new telecommunications systems, and software for synthesizing information, make a vast array of information available to an ever expanding number of organizational members. Management's exclusive control over knowledge is steadily declining, in part because of the downsizing of organizations and the decline of the number of layers in an organizational hierarchy. These trends, as well as issues surrounding the Web 2.0 and social networking, mean that it is increasingly important that we understand how informal knowledge networks impact the generation, capturing, storing, dissemination, and application of knowledge. This innovative book provides a thorough analysis of knowledge networks, focusing on how relationships contribute to the creation of knowledge, its distribution within organizations, how it is diffused and transferred, and how people find it and share it collaboratively.
Most common definitions of the information system fail to clearly separate the notions of information and knowledge, and these terms are generally used quite loosely. This is particularly the case for projects dealing with digital information systems (DIS) using applications of Web 2.0 and big data. This book presents the inherent risks linked to this ambiguity and studies the notion of the Enterpriseâs Information and Knowledge System (EIKS). It specifies the limits and conditions within which knowledge can be considered as an object and treated as an object in a DIS. EIKSs allow data exchanges, but also ensure how they are interpreted. They become actual knowledge systems.
Domain analysis is the process of studying the actions, knowledge production, knowledge dissemination, and knowledge-base of a community of commonality, such as an academic discipline or a professional community. The products of domain analysis range from controlled vocabularies and other knowledge organization systems, to scientific evidence about the growth and sharing of knowledge and the evolution of communities of discourse and practice.In the field of knowledge organization- both the science and the practice- domain analysis is the basic research method for identifying the concepts that will be critical building blocks for knowledge organization systems. This book will survey the theoretical rationale for domain analysis, present tutorials in the specific methods of domain analysis, especially with regard to tools for visualizing knowledge domains. * Focuses on the science and practice of organizing knowledge* Includes step-by-step instructions to enable the book to be used as a textbook or a manual for researchers
From the Publisher: Knowledge Management (KM) is strongly rooted in the discipline of Knowledge Engineering (KE), which in turn grew partly out of the artificial intelligence field. Despite their close relationship, however, many KM specialists have failed to fully recognize the synergy or acknowledge the power that KE methodologies, techniques, and tools hold for enhancing the state of the art in Knowledge Management.Knowledge Management: Learning from Knowledge Engineering addresses this vacuum. It gives concise, practical information and insights drawn from the author's many years of experience in the fields of expert systems and Knowledge Management. Based upon research, analyses, and illustrative case studies, this is the first book to integrate the theory and practice of artificial intelligence and expert systems with the current organizational and strategic aspects of Knowledge Management.The time has come for Knowledge Management professionals to appreciate the synergy between their work and the work of their counterparts in Knowledge Engineering. Knowledge Management: Learning from Knowledge Engineering is the ideal starting point for those in KM to learn from and exploit advances in that field, and thereby advance their own.
As the baby boomer generation approaches retirement age, many organizations are facing the potential crisis of lost knowledge. Devised to help those organizations who are dependent on the accumulated knowledge of stakeholders, this book details a proactive approach to knowledge retention. Written by Jay Liebowitz, one of the most sought after knowledge management experts, this text explains how to identify at risk knowledge areas, and then demonstrates how to keep those areas from becoming knowledge vacuums. To reinforce his points, the book contains case studies from The Aerospace Corporation, Chevron, and Knowledge Harvesting Inc., which have become models for the implementation of knowledge retention strategies
The rapidly growing demand for online courses and supporting technology has resulted in a plethora of structural and functional changes and challenges for universities and colleges. These changes have led many distance education providers to recognize the value of understanding the fundamental concepts of both e-learning and knowledge management (KM)including the e-learning economic model and how to change the current culture of delivery system providers. Supplying a complete examination of the synergy between KM and e-learning, Knowledge Management and E-Learning begins by considering KM practices, techniques, and methodologies in e-learning. These chapters explain how knowledge capture, retention, transfer, and sharing can help enhance the e-learning experience. Edited and written by leading authorities in the fields of knowledge management and e-learning, the book contains international case studies that illustrate the applications of KM to e-learning in businesses, government agencies, and universities in the United States, Canada, Mexico, United Kingdom, Europe, and Asia. The text is divided into four parts: Setting the Stage Methodologies and Techniques Case Studies and Applications Industry Perspectives This groundbreaking reference discusses the use of digital media engagement and social media to enhance the e-learning experience through the ability to share knowledge among various communities and individuals. It details key KM and social networking methodologies, trends, and technologies. The text concludes with a summary of current and emerging trends by those at the forefront of this rapidly evolving field.
Edited by Jussi Kantola, the founding faculty member of the worlds first university Knowledge Service Engineering Department at Korea Advanced Institute of Science and Technology, and Waldemar Karwowski from the Department of Industrial Engineering and Management Systems at UCF, Knowledge Service Engineering Handbook defines what knowledge services engineering means and how it is different from service engineering and service production. This groundbreaking handbook explores recent advances in knowledge service engineering from the accomplished researchers and practitioners in this field from around the world and provides engineering, systemic, industry, and consumer use viewpoints to knowledge service systems and engineering paradigms. The handbook outlines how to acquire and utilize knowledge in the 21st century presenting multiple cultural aspects including US, European, and Asian perspectives. Organized into four parts, it begins with an introduction to the main concepts of knowledge services. It then explores data, information and knowledge based engineering methods and applications that can be used to develop knowledge services, followed by discussions of the importance of human networks in knowledge services. The handbook concludes with descriptions of high-performance knowledge service systems. This structure allows different uses: the information can be looked up as needed or read in the order presented. As with any new field, the excitement lies in seeing how to combine these advances in data, information, and human parts of knowledge services in the future. While most books on this subject concentrate on data, information, or knowledge, this handbook integrates coverage of all three, thus providing a complete examination of sustainable knowledge services. The handbook has been carefully designed to be of use to professionals who develop new knowledge services and related businesses, for academic researchers and lecturers to start new research projects, and for students studying knowledge services, knowledge service production, and knowledge service business.
Within an IT framework, this book discusses creation, protection, development, sharing, and management of information and intellectual assets through the use of business intelligence and other knowledge sharing and analytical techniques.
PART ONE: EPISTEMOLOGICAL FOUNDATIONS 1. Introduction 2. Knowing and Organizing 3. Studying Organizational Knowledge PART TWO: ORGANIZATIONAL KNOWLEDGE IN ACTION 4. Tradition and Innovation at Fiat Auto 5. Knowledge-in-the-Making: The 'Construction' of Fiat Melfi's Factory 6. Breakdowns and Bottlenecks: Capturing the Learning Dynamics on the Assembly Line 7. Sense Making on the Shop Floor: The Narrative Dimension of Organizational Knowledge PART THREE: BUILDING A THEORY OF KNOWLEDGE IN ORGANIZATIONS 8. Action, Content, and Time: A Processual Model of Knowing and Organizing 9. Re-thinking Knowledge in Organizations
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