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<p>Last updated at: 2006-03-13 22:51:43 By user: PeterYim</p> <p><b>New page</b></p><div>= Conor Shankey =<br /> <br /> Visual Knowledge<br /> <br /> Vancouver, B.C., Canada <br /> <br /> http://www.visualknowledge.com/ <br /> <br /> '''Conor Shankey''' is the founder and CEO of Visual Knowledge. Visual<br /> Knowledge is an enterprise class ontology life cycle management platform and<br /> inference engine that enables the development of Lego like agent based systems.<br /> Visual Knowledge servers consists of active semantic agents that represent<br /> active ontological elements such as concepts, properties, axioms and<br /> transformations. The meta, meta layers of Visual Knowledge enable the<br /> platform to support different ontological and meta standards and the<br /> system is also fully compliant with OWL and RDF. <br /> <br /> Key capabilities of Visual Knowledge are: <br /> <br /> # The ability federate ontologies and knowledge bases <br /> # Semantic change management and versioning of ontological concepts and ontologies <br /> # Configurable micro inference models <br /> # Integrated transaction and multi-threading <br /> # Micro kernel that mitigates mustering of agents up into Java or upper languages <br /> <br /> === History ===<br /> <br /> In 1990 through 1996 Visual Knowledge was commissioned to develop a new<br /> kind<br /> of enterprise platform for a power utility to replace key mainframe<br /> systems<br /> that did work management, maintenance scheduling, management<br /> accounting,<br /> etc.. The first production version of Visual Knowledge (version 3) was<br /> a<br /> multi-user, transactional frame system, similar to Protégé except<br /> designed<br /> to let domain experts collaboratively build ontologies and axioms for<br /> resource scheduling and to serve as the underlying infrastructure for<br /> the<br /> enterprise. The production system managed an ontology with<br /> approximately<br /> 15,000 classes representing physical and resource systems and<br /> procedures,<br /> 3,000 rule sets and a few gigabytes of &quot;instances&quot;. The system used<br /> ontologies of procedural classes models that could assemble work orders<br /> and<br /> identify possible resources and was benchmarked to support up to 1200<br /> concurrent users. The system was implemented to interface with<br /> mainframe<br /> systems built in IMS and DB2 during phase out and integration. The<br /> production system was rolled out to one region but the internal IT<br /> organization was not comfortable in supporting the platform and scaling<br /> up<br /> it's use. <br /> <br /> From 1996 through 2000 Visual Knowledge was advanced to become a<br /> platform in<br /> the aviation world and was utilized to develop trip plans, schedule<br /> crews<br /> and aircraft, automate profit and loss estimates on charters and<br /> schedule<br /> aircraft maintenance. Ontological modeling evolved from using rules<br /> based<br /> semantics to an agent based axiom toolkit for higher order knowledge<br /> representation and inferencing. The system was deployed to several<br /> charter<br /> companies and private operators. <br /> <br /> From 1999 through 2001 Visual Knowledge was utilized to develop several<br /> B2B<br /> systems including a foreign currency exchange, semantic matching engine<br /> and<br /> payment fulfillment system. Unfortunately with the .com crash many of<br /> our<br /> industrial solution partners faded away. <br /> <br /> From 2001 to present a biological system known as [http://www.visualknowledge.com/cgi-bin/gwi.exe [[BioCAD]]] was developed<br /> on<br /> top of Visual Knowledge to enable biologist to model gene, proteins,<br /> interactions, organisms, signaling pathways and experimental protocols.<br /> The<br /> scale of Visual Knowledge was pushed to support models with around 30<br /> million concepts and several hundred million assertions on lower end<br /> servers. A transactional experimental system called <br /> [http://www.kinexus.ca [[KiNET]]] was developed as a production system on top of<br /> [http://www.visualknowledge.com/cgi-bin/gwi.exe [[BioCAD]]] to enable the analysis of thousands of experiments in<br /> multi-dimensional manner. <br /> <br /> From 2003 to present the fifth generation of Visual Knowledge was<br /> developed<br /> and the kernel or engine was migrated from an active object database<br /> down<br /> into our own native semantic persistence and transaction engine. This<br /> now<br /> enables us to achieve a level of scale required for the very large<br /> scale of<br /> knowledge bases that occur in even conventional technology today. We<br /> (finally) successfully developed and stabilized a packaging and version<br /> management system so that ontologies and knowledge based could be<br /> rationally<br /> changed in a federated environment of many servers. In the past year we<br /> built an OWL and RDF compliant capability on top of Visual Knowledge so<br /> that<br /> the system could readily absorb and manage ontologies represented in<br /> OWL,<br /> knowledge asserted in RDF and provide OWL DL and OWL Full compliant<br /> inferencing. <br /> <br /> We are interested in the idea of building an experimental platform for<br /> playing with and testing more than one KR language and once with many<br /> upper<br /> and lower ontologies. <br /> <br /> [[Category:Person]]<br /> <br /> <br /> <br /> </div>

imported>PeterYim