Business Process Automation Using Rules Standards and the Semantic Web
Paul Haley
Executive Vice President
Haley Systems
March 7, 2007
10:00 AM - 11:00 AM
Level: Introductory/All Levels
Enterprise modelers are increasing interested in the
semantic integrity and implementation-independence of the business models
that underlay service-oriented architectures and object or data models
used in applications. The semantic web framework offers the most mature
and broadly accepted semantic modeling capabilities and the most logically
clean and capable formalisms for rules available. This framework include
OWL, the web ontology language and the semantic web rule language (SWRL)
and its first-order logic extension (SWRL-FOL).
This presentation demonstrates an upper ontology that provides a semantic core (e.g., general purpose units, time, the calendar, numbers, entities) for OWL ontologies and the linguistic augmentation of OWL ontologies such that human language (e.g., English) sentences can be formally understood and translated into SWRL-FOL for execution by a general purpose inference engine.
The demonstration is couched in a financial services application accessed through a web browser, the behavior of which is determined by sentences using a vocabulary defined using the rooted OWL ontology.
This presentation demonstrates an upper ontology that provides a semantic core (e.g., general purpose units, time, the calendar, numbers, entities) for OWL ontologies and the linguistic augmentation of OWL ontologies such that human language (e.g., English) sentences can be formally understood and translated into SWRL-FOL for execution by a general purpose inference engine.
The demonstration is couched in a financial services application accessed through a web browser, the behavior of which is determined by sentences using a vocabulary defined using the rooted OWL ontology.
Paul V. Haley is the Executive Vice President and CTO at
Haley Systems. He has been an innovator in knowledge-based systems technology
and application development since the early 1980s, before the emergence
of the artificial intelligence (AI) industry and business rules technology.
Leveraging his technical expertise, Mr. Haley has more than 20 years
of start-up, executive management, innovation and development experience
with high technology companies.
Mr. Haley founded Haley Systems in 1989. Prior to launching the Company, he co-founded the Intelligent Technology Group (ITG) and led its Intelligent Software Technology Partner in applying AI to the financial services industry. As Vice President of Technology, Mr. Haley helped ITG grow to more than 100 employees and $10 million in revenues. Prior to ITG, Mr. Haley served as Chief Scientist for Inference Corporation, managing the development of the company's main product and personally implementing its rule-based architecture. Mr. Haley also served as a consultant to Digital Equipment Corporation (DEC), where he delivered some of the first industrial knowledge-based systems and helped inaugurate DEC's renowned Expert System Training Program. Mr. Haley began his career in AI while at Carnegie Mellon University, where he refined and applied the Rete Algorithm (now the backbone of all high-performance business rules engines) in several of the first commercially successful expert systems.
Mr. Haley earned a master of science in computer science from the University of Washington and an undergraduate degree in physics and astronomy from the University of Virginia.
Mr. Haley founded Haley Systems in 1989. Prior to launching the Company, he co-founded the Intelligent Technology Group (ITG) and led its Intelligent Software Technology Partner in applying AI to the financial services industry. As Vice President of Technology, Mr. Haley helped ITG grow to more than 100 employees and $10 million in revenues. Prior to ITG, Mr. Haley served as Chief Scientist for Inference Corporation, managing the development of the company's main product and personally implementing its rule-based architecture. Mr. Haley also served as a consultant to Digital Equipment Corporation (DEC), where he delivered some of the first industrial knowledge-based systems and helped inaugurate DEC's renowned Expert System Training Program. Mr. Haley began his career in AI while at Carnegie Mellon University, where he refined and applied the Rete Algorithm (now the backbone of all high-performance business rules engines) in several of the first commercially successful expert systems.
Mr. Haley earned a master of science in computer science from the University of Washington and an undergraduate degree in physics and astronomy from the University of Virginia.