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A Formal Context Representation Framework for Network-Enabled Cognition

A Formal Context Representation Framework for Network-Enabled Cognition
A Formal Context Representation Framework for Network-Enabled Cognition
Network-accessible resources are inherently contextual with respect to the specific situations (e.g., location and default assumptions) in which they are used. Therefore, the explicit conceptualization and representation of contexts is required to address a number of problems in Network- Enabled Cognition (NEC). We propose a context representation framework to address the computational specification of contexts. Our focus is on developing a formal model of context for the unambiguous and effective delivery of data and knowledge, in particular, for enabling forms of automated inference that address contextual differences between agents in a distributed network environment. We identify several components for the conceptualization of contexts within the context representation framework. These include jurisdictions (which can be used to interpret contextual data), semantic assumptions (which highlight the meaning of data), provenance information and inter-context relationships. Finally, we demonstrate the application of the context representation framework in a collaborative military coalition planning scenario. We show how the framework can be used to support the representation of plan-relevant contextual information.
context model, context representation, context-sensitive processing, semantic web, world wide web
Bao, Jie
19988b37-501b-4199-8d2a-a04190580e81
Smart, Paul R
cd8a3dbf-d963-4009-80fb-76ecc93579df
Mott, David
bf0779fe-ac61-4fac-965e-a774d0d3437d
Braines, Dave
09e96745-c478-4a3d-9a3b-46e0f0e3ac18
Bao, Jie
19988b37-501b-4199-8d2a-a04190580e81
Smart, Paul R
cd8a3dbf-d963-4009-80fb-76ecc93579df
Mott, David
bf0779fe-ac61-4fac-965e-a774d0d3437d
Braines, Dave
09e96745-c478-4a3d-9a3b-46e0f0e3ac18

Bao, Jie, Smart, Paul R, Mott, David and Braines, Dave (2010) A Formal Context Representation Framework for Network-Enabled Cognition. 4th Annual Conference of the International Technology Alliance (ACITA'10), United Kingdom. 14 - 16 Sep 2010.

Record type: Conference or Workshop Item (Paper)

Abstract

Network-accessible resources are inherently contextual with respect to the specific situations (e.g., location and default assumptions) in which they are used. Therefore, the explicit conceptualization and representation of contexts is required to address a number of problems in Network- Enabled Cognition (NEC). We propose a context representation framework to address the computational specification of contexts. Our focus is on developing a formal model of context for the unambiguous and effective delivery of data and knowledge, in particular, for enabling forms of automated inference that address contextual differences between agents in a distributed network environment. We identify several components for the conceptualization of contexts within the context representation framework. These include jurisdictions (which can be used to interpret contextual data), semantic assumptions (which highlight the meaning of data), provenance information and inter-context relationships. Finally, we demonstrate the application of the context representation framework in a collaborative military coalition planning scenario. We show how the framework can be used to support the representation of plan-relevant contextual information.

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More information

Published date: 14 September 2010
Additional Information: Event Dates: 14th - 16th September 2010
Venue - Dates: 4th Annual Conference of the International Technology Alliance (ACITA'10), United Kingdom, 2010-09-14 - 2010-09-16
Keywords: context model, context representation, context-sensitive processing, semantic web, world wide web
Organisations: Web & Internet Science

Identifiers

Local EPrints ID: 271466
URI: https://eprints.soton.ac.uk/id/eprint/271466
PURE UUID: 3318dc7a-b8c4-48d0-bd60-13f303288303
ORCID for Paul R Smart: ORCID iD orcid.org/0000-0001-9989-5307

Catalogue record

Date deposited: 11 Aug 2010 09:57
Last modified: 06 Jun 2018 12:46

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Contributors

Author: Jie Bao
Author: Paul R Smart ORCID iD
Author: David Mott
Author: Dave Braines

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