Semantic-based knowledge management tools

This advanced title provides readers with critical steps and tools for developing a semantic based knowledge management system. Emergent semantics provides a natural solution as its definition is based on a process of finding stable agreements; constant evolution is part of the model and stable states, provided they exist, are autonomously detected.

Also, emergent semantics techniques can be applied to detect and even predict changes and evolution in the state of an organization or a community. This book assembles 28 chapters that detail how to develop a semantic-based knowledge management system. Since he is secretary of the IFIP 2. Offer does not apply to e-Collections and exclusions of select titles may apply. Offer expires June 30, Browse Titles. DOI: Hardcover: Available.

E-Book: Multi-User License. The massive quantity of data, information, and knowledge available in digital form on the web or within the organizational knowledge base requires a more effective way to control it. The Semantic Web and its growing complexity demands a resource for the understanding of proper tools for management.

Semantic Knowledge Management: An Ontology-Based Framework addresses the Semantic Web from an operative point of view using theoretical approaches, methodologies, and software applications as innovative solutions to true knowledge management. This advanced title provides readers with critical steps and tools for developing a semantic based knowledge management system. In the last few years, many international organizations and enterprises have designed, developed and deployed advanced knowledge management systems that are now vital for their daily operations.

The Semantic Web perspective has added to knowledge management systems a new capability: reasoning on ontology-based metadata.

In many application fields, however, data semantics is getting more and more context- and time-dependent, and cannot be fixed once and for all at design time. Recently, some novel knowledge generation and access paradigms such as augmented cognition, case-study-based reasoning and episodic games have shown the capability of accelerating the kinetics of ideas and competence transmission in creative communities, allowing organizations to exploit the high interactive potential of broadband and mobile network access.

In this new scenario, traditional design-time data semantics frozen in database schemata or other metadata is only a starting point. Online, emergent semantics is playing an increasingly important role. The supply of semantics is twofold: firstly, human designers are responsible for providing initial semantic mappings between information and its environment used for context-aware access.

Secondly, the meaning of data is dynamically augmented and adapted taking into account organizational processes and, in general, human cognition. The Semantic Web paradigm was proposed to tackle some of the problems related to implicit representation of data semantics affecting Web-related data items e.

Today, advanced knowledge management platforms incorporate on-demand production of Semantic-Web style metadata based on explicit, shared reference systems such as ontology vocabularies, which consist of explicit though partial definitions of the intended meaning for a domain of discourse. It is widely recognized that business ontologies can be unstable and that managing ontology evolution and alignment is a constant challenge, as well as a heavy computational burden.

Indeed, this problem cannot be tackled without realizing that integrating initial, design-time semantics with emergent, interaction-time semantics is as much an organizational, business-related process as a technology based one. KIWI envisioned a distributed community composed of information agents sharing content, e. In this community, agents and human actors are able to cooperate in building new semantics based on their interaction and adding it to content, irrespective of the source and vocabulary of the initial semantics of the information.

The KIWI vision considers emergent semantics constructed incrementally in this way as a powerful tool for increasing content validity and impact. The observation that emergent semantics results from a self-organizing process has also some interesting consequences on the stability of the content from the business management and social sciences point of view. Also, this perspective promises to address some of the inherently hard problems of classical ways of building semantics in information systems.

Emergent semantics provides a natural solution as its definition is based on a process of finding stable agreements; constant evolution is part of the model and stable states, provided they exist, are autonomously detected. Also, emergent semantics techniques can be applied to detect and even predict changes and evolution in the state of an organization or a community. The contents are structured in three sections, the first one is completely related to the KIWI project, the activities, the theoretical results and the prototypes developed are presented and discussed.

The work was developed in a methodological framework that represents the phases and the tools for an effective introduction of a semantic-based knowledge management platform in a community.

The second one presents other theoretical works related to the introduction of the semantic description of knowledge resource in organization or in technological environment.