By Paul Warren, John Davies, Elena Simperl
Knowledge and knowledge are one of the greatest resources of companies and companies. besides the fact that, successfully coping with, preserving, gaining access to, and reusing this intangible treasure is hard. info overload makes it tough to target the knowledge that actually issues; the truth that a lot company wisdom in basic terms is living in staff’ heads heavily hampers reuse.
The paintings defined during this ebook is encouraged through the necessity to elevate the productiveness of data paintings. in response to effects from the EU-funded energetic venture and complemented by means of contemporary similar effects from different researchers, the appliance of 3 methods is gifted: the synergy of net 2.0 and semantic expertise; context-based details supply; and using expertise to help casual person approaches. The contributions are equipped in 5 elements. half I contains a common creation and an outline of the possibilities and demanding situations confronted by means of corporations in exploiting net 2.0 functions. half II appears on the applied sciences, and likewise a few methodologies, built in lively. half III describes how those applied sciences were evaluated in 3 case reports in the undertaking. half IV starts off with a bankruptcy describing the significant marketplace developments for wisdom administration suggestions, after which incorporates a variety of chapters describing paintings complementary to energetic. eventually, half V attracts conclusions and exhibits additional components for research.
Overall, this ebook more often than not goals at researchers in academia and searching for a state of the art review of using semantic and internet 2.0 applied sciences for wisdom administration and private productiveness. Practitioners in also will profit, particularly from the case reports which spotlight state-of-the-art functions in those fields.
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Additional resources for Context and Semantics for Knowledge Management: Technologies for Personal Productivity
1 On the Semantic Web, the classic trade-offs regarding expressivity have been decidability and complexity. For a language to be decidable, a reasoner can be implemented such that all questions that can be asked against a knowledge base that are expressed using that language have an answer. Decidability as a property of languages is highly desirable: it guarantees that all questions that can be asked can be answered, and that the associated reasoning algorithms are effectively implementable. Research in Description Logics explores the borders of decidability.
Openly developed ontologies: developed by a large, open community of users, who are free to contribute to the content of the ontology. The ontology, as a result of continuous refinements and extensions, emerges to a commonly agreed, widely accepted representation of the domain of interest. The evolution of the Open Directory classification is a good example for collaborative, Web-based ontology development: the core structure of the topic classification, originally proposed by Yahoo! com/) and used in slightly modified form 36 B.
The boundary between “business intelligence” and “social intelligence” is no longer a clear one, and this leads to some interesting tensions in emerging business models. Integrating data from large numbers of sources and realising the potential for global reach to harness business and social intelligence poses new challenges for process and data management in dynamic use contexts. audiences spread across vast geographical areas. Hal Varian’s Information Rules developed the idea of developing value propositions based on the versioning of information for different audiences.