Ontolog Series on "Database And Ontology" (Session-11) - Thu 18-Oct-2007    (12T7)

Conference Call Details    (14FU)

Attendees    (14GL)

Background    (14GV)

This is the 11th event of the "Database and Ontology series" of talks and discussions, during which this community will be exploring the landscape, issues and interactions between databases and ontologies.    (14GW)

This is a community-driven set of activities, and is probably long overdue. On 15-Aug-2006, TatianaMalyuta (who just joined the community after participating at our 23-Jul-2006 face-to-face workshop at Stanford, brought up her request for the Ontolog Forum to delve into the subject of "Database and Ontologiy." An almost unprecedented flurry of online responses were received from the community. It was decided that we could systematically pursue the subject by mounting a mini-series on the matter at hand.    (14GX)

A planning meeting for what has started out as a mini-series took place on 31-Aug-2006. MatthewWest was invited to champion the effort, and a "Program & Technical Advisory Team" was formed, comprising MatthewWest (Lead), AdrianWalker, AtillaElci, ChrisPartridge, LeoObrst, PeterYim, SusieStephens & TatianaMalyuta.    (14GY)

See also: DatabaseAndOntology (the 'project' homepage for this series)    (14GZ)

The community is requested to contribute their thoughts by posting to [ontolog-forum] or to the DatabaseAndOntology wiki page (and/or its subpages). We hope to accumulate and synthesize the knowledge gathered and compile it into a written deliverable (a paper or even a handbook) that we could publish this collaboratively authored work to other relevant media and channels (like relevant conferences or the wikipedia.)    (14H0)

Agenda & Proceedings: "Database And Ontology" Series Session-11    (14H1)

Title: A Scalable RDBMS-Based Inference Engine for RDFS/OWL    (14HA)

Abstract (by AlanWu):    (14HB)

Inference engine is a key component of Semantic Web technologies. As Semantic Web technologies is gaining traction, OWL ontologies and RDF graphs are growing increasingly in size. Users and application developers of semantic web technologies therefore need an efficient and scalable inference engine that is not bound by main-memory size. Another critical requirement is that inferred knowledge together with the original knowledge base should be made available in a query-friendly format. Traditional RDBMS technology has proven to be a suitable platform for building such an inference engine. In this talk, we present an architecture for a scalable RDBMS-based inference engine, discuss expressivity vs. efficiency tradeoffs, explore an interesting separation of T-Box and A-Box reasoning, and finally show the inference engine performance using benchmark ontologies.    (14HC)

About the Invited Speaker:    (14HD)

[picture of Dr. Zhe (Alan) Wu] http://ontolog.cim3.net/file/work/DatabaseAndOntology/2007-10-18_AlanWu/ZheWu_2007a.jpg    (14IK)

Zhe (a.k.a Alan) Wu received his PhD degree in computer science from the University of Illinois at Urbana-Champaign in 2001. He received his B.E. degree from the Special Class for Gifted Young, University of Science & Technology of China in 1996. He is currently a Principal Member of Technical Staff working in New England Development Center, Oracle. As an Oracle representative, he served on UDDI standard specification technical committee from Aug. 2003 to Sept. 2005. His work and research interests are in semantic web technologies, logical inferencing, database, web services, nonlinear optimization, computer security and computer networks.    (14HE)

Resources    (14HF)

Questions, Answers & Discourse:    (14HK)

Audio Recording of this Session    (14HT)