A Knowledge Management System Embedded in the New Semantic Technologies

Abstract

There is a large interest in organizational knowledge in the context of transition to knowledge economy, where knowledge is viewed as the main source of sustainable competitive advantage. Although knowledge management (KM) is primarily concerned with how people and organizations use their knowledge assets, one way to do this efficiently is to employ technology to facilitate the KM processes (Alavi, 1999). Consistent with the growing interest in organizational knowledge and KM, many ICT researchers have been promoting a class of information systems, referred to as Knowledge Management Systems (KMSs). The objective of a KMS is to support knowledge capturing, categorizing, storing, searching, distributing and application within organizations. Technical advances in computers’ processing and storage capacity, together with linking these computers into networks of distributed nodes, have greatly increased the organizations’ capability to deliver goods and services. Along with these capabilities we need quality, accuracy, responsiveness and capacity. Particular topics of interest on KMSs include among others: Organizational knowledge management approaches, Information management challenges, Service Oriented Architecture (SOA), software environments, Semantic web services environments, Information modeling and the representation of semantics, Intelligent software tools and services, Information management systems in practice. Semantics is the study of meaning. Semantic Technologies (STs) are distributed software technologies that make the meaning more explicit, principally so that it can be understood by computers. New Semantic Technologies (NSTs) will dramatically influence enterprise’s architecture and the engineering of new systems and infrastructure capabilities, so that they act as disruptive technologies (so innovative that they have the potential to completely change the way we do business) on capturing and sharing next generation knowledge among workers and organizations in the new economy. NSTs are tools that represent meanings, associations, theories, and know-how about the application of things, separately from data and program codes. These systems must be designed as distributed systems, with the ability to combine different knowledge-based techniques (with the purpose of acquiring and processing information and knowledge), based on approximate reasoning methods (Muller, 1996; Lin, 2008). NSTs will better emulate the human decision-making process, also characterized by imprecise and time-varying knowledge (Knight & Passino, 1987; Barachini, 1990; Dubois et al., 1991; Qian, 1992; Nebel & Backstrom, 1994). Time restrictions are not