Ontology applications and implementations discussion lead by Mr. Duane Nickull (Adobe Systems) and Mr. Kurt Conrad (The Sagebrush Group) on 12-15-2005
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ONTOLOG is an open, international, virtual community of practice working on the application and adoption of ontological engineering and semantic technologies.
Beschreibung
vor 18 Jahren
* Organized and Co-Moderated by:
Duane Nickull (Adobe Systems) and Kurt Conrad (The Sagebrush Group). Topic first proposed by Duane Nickull and Kurt Conrad on 2005.10.06
* Date
December 15th, 2006
* Panelists
LeoObrst, MITRE
ItzhakRoth, Unicorn Solutions
AdrianWalker, Reengineering
* Details on ONTOLOG Wiki page
See http://ontolog.cim3.net/cgi-bin/wiki.pl?ConferenceCall_2005_12_15
* Abstracts
Semantic Technologies in Bioinformatics
By ItzhakRoth, Unicorn Solutions, Inc.
The initiative funded by a division of the NIH (National Institute of Health) aims to create an environment that provides advanced information technology support in the production, analysis, archiving, and exchange of scientific data for a diverse community of life science researchers. The target system integrates highly diverse bio-science data from numerous disparate sources, enabling access to a broad array of reference data (e.g., genes, proteins, genomics sequences, SNP, human haplotype etc.) combined with experimental data from about 20 different experimentation platforms.
Semantic Interoperability via Business Rules in Open Vocabulary, Executable English
By AdrianWalker, Reengineering
New technologies are currently advancing the Semantic Web, based on the data semantics of XML and RDF. An advantage of RDF is that data from diverse sources can, in principle, be freely merged and repurposed. Yet we cannot expect meaningful results from simply merging previously unseen data under an existing application. We need to be able to easily state new meanings at the application level.
The presentation will argue that current approaches to semantics for machine-machine interoperability need to be extended, in order to capture real world meanings for human-machine communication. We show how this can be done in a system that combines inference based on a model theory of stratified nonmontonic logic [1], with support for lightweight, open vocabulary English. One can think of this as realizing application level semantics.
Duane Nickull (Adobe Systems) and Kurt Conrad (The Sagebrush Group). Topic first proposed by Duane Nickull and Kurt Conrad on 2005.10.06
* Date
December 15th, 2006
* Panelists
LeoObrst, MITRE
ItzhakRoth, Unicorn Solutions
AdrianWalker, Reengineering
* Details on ONTOLOG Wiki page
See http://ontolog.cim3.net/cgi-bin/wiki.pl?ConferenceCall_2005_12_15
* Abstracts
Semantic Technologies in Bioinformatics
By ItzhakRoth, Unicorn Solutions, Inc.
The initiative funded by a division of the NIH (National Institute of Health) aims to create an environment that provides advanced information technology support in the production, analysis, archiving, and exchange of scientific data for a diverse community of life science researchers. The target system integrates highly diverse bio-science data from numerous disparate sources, enabling access to a broad array of reference data (e.g., genes, proteins, genomics sequences, SNP, human haplotype etc.) combined with experimental data from about 20 different experimentation platforms.
Semantic Interoperability via Business Rules in Open Vocabulary, Executable English
By AdrianWalker, Reengineering
New technologies are currently advancing the Semantic Web, based on the data semantics of XML and RDF. An advantage of RDF is that data from diverse sources can, in principle, be freely merged and repurposed. Yet we cannot expect meaningful results from simply merging previously unseen data under an existing application. We need to be able to easily state new meanings at the application level.
The presentation will argue that current approaches to semantics for machine-machine interoperability need to be extended, in order to capture real world meanings for human-machine communication. We show how this can be done in a system that combines inference based on a model theory of stratified nonmontonic logic [1], with support for lightweight, open vocabulary English. One can think of this as realizing application level semantics.
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