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Toward generic, immersive, and collaborative solutions to the data interoperability problem which target end-users
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Conference on Information and Knowledge Management archive
Proceeding of the 2nd international workshop on Ontologies and nformation systems for the semantic web table of contents
Napa Valley, California, USA
SESSION: Session 1 table of contents
Pages 83-88  
Year of Publication: 2008
ISBN:978-1-60558-255-9
Authors
Arturo J. Sánchez-Ruíz  University of North Florida, Jacksonville, FL, USA
Karthikeyan Umapathy  University of North Florida, Jacksonville, FL, USA
Pat Hayes  Florida Institute for Human and Machine Cognition (IHMC), Pensacola, FL, USA
Sponsors
ACM: Association for Computing Machinery
SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
SIGIR: ACM Special Interest Group on Information Retrieval
Publisher
ACM  New York, NY, USA
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ABSTRACT

In this position paper we describe our vision of a "just-in-time" approach to the Data Interoperability Problem (a.k.a. INTEROP.) It empowers data stakeholders (e.g. data producers and data consumers) with integrated tools to interact and collaborate with each other while directly manipulating visual representations of their data in an immersive environment (e.g. implemented via Second Life.) The semantics of these visual representations and the operations associated with the data are supported by ontologies defined using the Common Logic Framework (CL). Data operations gestured by the stakeholders, through their avatars, are translated to a variety of generated resources such as multi-language source code, visualizations, web pages, and web services. The generality of the approach is supported by a plug-in architecture which allows expert users to customize tasks such as data admission, data manipulation in the immersive world, and automatic generation of resources. This approach is designed with a mindset aimed at enabling stake-holders from diverse domains to exchange data and generate new knowledge.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Arturo J. Sánchez-Ruíz: colleagues
Karthikeyan Umapathy: colleagues
Pat Hayes: colleagues