PSL and SWSL Michael Gruninger Institute for Systems Research University of Maryland Michael Gruninger Institute for Systems Research University of Maryland.

Slides:



Advertisements
Similar presentations
T YPE I SOMORPHISM O LA M AHMOUD S UPERVISED BY : D R. M ARCELO F IORE UNIVERSITY OF CAMBRIDGE Computer Laboratory Theory & Semantics Group I NTRODUCTION.
Advertisements

Upper Ontology Summit March 14, 2006 Michael Gruninger Semantic Technologies Laboratory University of Toronto.
Dr. Leo Obrst MITRE Information Semantics Information Discovery & Understanding Command & Control Center February 6, 2014February 6, 2014February 6, 2014.
1 FLOWS : A First-Order Logic Ontology for Web Services Michael Gruninger Rick Hull Sheila McIlraith.
1 Evaluating Reasoning Systems: Ontology Languages Michael Grunginger, U. Toronto Conrad Bock, U.S. NIST February 22 nd, 2007.
WSDL Mapping to RDF/Semantic Web July, 2004 London, England F2F.
1 ICS-FORTH & Univ. of Crete SeLene November 15, 2002 A View Definition Language for the Semantic Web Maganaraki Aimilia.
Upper Ontology Summit March 15, 2006 Michael Gruninger Semantic Technologies Laboratory University of Toronto.
Semantics Static semantics Dynamic semantics attribute grammars
The Process Specification Language: Around the World in 80 Axioms Michael Gruninger Institute for Systems Research University of Maryland Michael Gruninger.
1 A Description Logic with Concrete Domains CS848 presentation Presenter: Yongjuan Zou.
Ontology From Wikipedia, the free encyclopedia In philosophy, ontology (from the Greek oν, genitive oντος: of being (part. of εiναι: to be) and –λογία:
ISBN Chapter 3 Describing Syntax and Semantics.
CS 355 – Programming Languages
Analyzing Minerva1 AUTORI: Antonello Ercoli Alessandro Pezzullo CORSO: Seminari di Ingegneria del SW DOCENTE: Prof. Giuseppe De Giacomo.
An Extensible System for Merging Two Models Rachel Pottinger University of Washington Supervisors: Phil Bernstein and Alon Halevy.
Language Specfication and Implementation - PART II: Semantics of Procedural Programming Languages Lee McCluskey Department of Computing and Mathematical.
Common Logic in Support of Metadata and Ontologies Open Forum 2005 on Metadata Registries 14:45 Track 1 14 April 2005 Harry S. Delugach Intelligent Systems.
CS 330 Programming Languages 09 / 18 / 2007 Instructor: Michael Eckmann.
Describing Syntax and Semantics
Knowledge Mediation in the WWW based on Labelled DAGs with Attached Constraints Jutta Eusterbrock WebTechnology GmbH.
Ontology Development Kenneth Baclawski Northeastern University Harvard Medical School.
Practical RDF Chapter 1. RDF: An Introduction
Knowledge Interchange Format Michael Gruninger National Institute of Standards and Technology
Status report of : Framework for generating ontologies ISO/IEC JTC 1/SC 32/WG 2 Interim Meeting, Redwood City, USA, November 17, 2010 Dongwon Jeong,
Of 39 lecture 2: ontology - basics. of 39 ontology a branch of metaphysics relating to the nature and relations of being a particular theory about the.
INF 384 C, Spring 2009 Ontologies Knowledge representation to support computer reasoning.
School of Computing FACULTY OF ENGINEERING Developing a methodology for building small scale domain ontologies: HISO case study Ilaria Corda PhD student.
1 MFI-5: Metamodel for Process models registration HE Keqing, WANG Chong State Key Lab. Of Software Engineering, Wuhan University
MPEG-7 Interoperability Use Case. Motivation MPEG-7: set of standardized tools for describing multimedia content at different abstraction levels Implemented.
An Algebra for Composing Access Control Policies (2002) Author: PIERO BONATTI, SABRINA DE CAPITANI DI, PIERANGELA SAMARATI Presenter: Siqing Du Date:
ISBN Chapter 3 Describing Semantics -Attribute Grammars -Dynamic Semantics.
LOGIC AND ONTOLOGY Both logic and ontology are important areas of philosophy covering large, diverse, and active research projects. These two areas overlap.
Translation Patterns to Specify Processes in the PSL Ontology Dr. A. Sánchez-Ruíz University of North Florida CIS Department Associate Professor and Coordinator.
Using Model-Theoretic Invariants for Semantic Integration Michael Gruninger NIST / Institute for Systems Research University of Maryland Michael Gruninger.
Advanced topics in software engineering (Semantic web)
Proposed NWI KIF/CG --> Common Logic Standard A working group was recently formed from the KIF working group. John Sowa is the only CG representative so.
Ontological Implications of Service- Oriented Architecture Michael Gruninger NIST / Institute for Systems Research University of Maryland.
The Process Specification Language (PSL): Theories and Applications Michael Grüninger and Christopher Menzel Journal Club Presentation Eric Rozell, Tetherless.
Semantically Processing The Semantic Web Presented by: Kunal Patel Dr. Gopal Gupta UNIVERSITY OF TEXAS AT DALLAS.
3.2 Semantics. 2 Semantics Attribute Grammars The Meanings of Programs: Semantics Sebesta Chapter 3.
Chapter 3 Part II Describing Syntax and Semantics.
Programming Languages and Design Lecture 3 Semantic Specifications of Programming Languages Instructor: Li Ma Department of Computer Science Texas Southern.
Artificial Intelligence 2004 Ontology
DAML+OIL: an Ontology Language for the Semantic Web.
Issues in Ontology-based Information integration By Zhan Cui, Dean Jones and Paul O’Brien.
Extending the MDR for Semantic Web November 20, 2008 SC32/WG32 Interim Meeting Vilamoura, Portugal - Procedure for the Specification of Web Ontology -
ISO/IEC JTC 1/SC 32 Plenary and WGs Meetings Jeju, Korea, June 25, 2009 Jeong-Dong Kim, Doo-Kwon Baik, Dongwon Jeong {kjd4u,
Computer Science CPSC 322 Lecture 22 Logical Consequences, Proof Procedures (Ch 5.2.2)
A Portrait of the Semantic Web in Action Jeff Heflin and James Hendler IEEE Intelligent Systems December 6, 2010 Hyewon Lim.
OWL Web Ontology Language Summary IHan HSIAO (Sharon)
CSC3315 (Spring 2009)1 CSC 3315 Languages & Compilers Hamid Harroud School of Science and Engineering, Akhawayn University
C HAPTER 3 Describing Syntax and Semantics. D YNAMIC S EMANTICS Describing syntax is relatively simple There is no single widely acceptable notation or.
Presented by Kyumars Sheykh Esmaili Description Logics for Data Bases (DLHB,Chapter 16) Semantic Web Seminar.
Interpreting the Object Constraint Presented by: Ed Kausmeyer.
Semantic Interoperability in GIS N. L. Sarda Suman Somavarapu.
1 Developing an Ontology of Ontologies for OOR Ontology Summit 2008 April 28-29, 2008 Michael Gruninger and Pat Hayes.
Semantic Web. P2 Introduction Information management facilities not keeping pace with the capacity of our information storage. –Information Overload –haphazardly.
Artificial Intelligence Logical Agents Chapter 7.
1 Representing and Reasoning on XML Documents: A Description Logic Approach D. Calvanese, G. D. Giacomo, M. Lenzerini Presented by Daisy Yutao Guo University.
SysML v2 Formalism: Requirements & Benefits
ece 627 intelligent web: ontology and beyond
Ontology From Wikipedia, the free encyclopedia
Web Ontology Language for Service (OWL-S)
Service-Oriented Computing: Semantics, Processes, Agents
Piotr Kaminski University of Victoria September 24th, 2002
Service-Oriented Computing: Semantics, Processes, Agents
Semantic Markup for Semantic Web Tools:
ONTOMERGE Ontology translations by merging ontologies Paper: Ontology Translation on the Semantic Web by Dejing Dou, Drew McDermott and Peishen Qi 2003.
Representations & Reasoning Systems (RRS) (2.2)
Presentation transcript:

PSL and SWSL Michael Gruninger Institute for Systems Research University of Maryland Michael Gruninger Institute for Systems Research University of Maryland

Goal Ontology for web services –Generic classes of services –Classes of constraints in service specifications ordering temporal occurrence triggers (state-based constraints) duration Language for web service specifications (SWSL) Ontology for web services –Generic classes of services –Classes of constraints in service specifications ordering temporal occurrence triggers (state-based constraints) duration Language for web service specifications (SWSL)

Approach Specify a first-order semantics for DAML-S concepts through PSL translation definitions Use the grammars associated with PSL classes as the abstract syntax for SWSL Specify a first-order semantics for DAML-S concepts through PSL translation definitions Use the grammars associated with PSL classes as the abstract syntax for SWSL

Semantics Why do we want a first-order model theory? –inference (sound and complete with respect to models) –easily integrated with other ontologies (which are all first-order) Why do we want a first-order model theory? –inference (sound and complete with respect to models) –easily integrated with other ontologies (which are all first-order)

Reasoning Problems Reasoning problems for web service specifications –Consistency of constraints –Composability of services –Search queries Reasoning problems for web service specifications –Consistency of constraints –Composability of services –Search queries

Formal Properties of PSL The meaning of terms in the ontology is characterized by models for first-order logic. The PSL Ontology has a first-order axiomatization of the class of models. Classes in the ontology arise from classification of the models with respect to invariants (properties of the models preserved by isomorphism). Process descriptions are specified by definable types for elements in the models. The meaning of terms in the ontology is characterized by models for first-order logic. The PSL Ontology has a first-order axiomatization of the class of models. Classes in the ontology arise from classification of the models with respect to invariants (properties of the models preserved by isomorphism). Process descriptions are specified by definable types for elements in the models.

Organization of PSL PSL is a modular, extensible ontology capturing concepts required for process specification There are currently 300 concepts across 50 extensions of a common core theory (PSL-Core), each with a set of axioms written using the Knowledge Interchange Format. Two kinds of extensions: Core theories Definitional extensions PSL is a modular, extensible ontology capturing concepts required for process specification There are currently 300 concepts across 50 extensions of a common core theory (PSL-Core), each with a set of axioms written using the Knowledge Interchange Format. Two kinds of extensions: Core theories Definitional extensions

PSL Core Theories

Additional Core Theories Duration Subactivity Occurrence Ordering Iterated Occurrence Ordering Resource Requirements Resource Sets Activity Performance Duration Subactivity Occurrence Ordering Iterated Occurrence Ordering Resource Requirements Resource Sets Activity Performance

Definitional Extensions Preserving semantics is equivalent to preserving models of the axioms. – preserving models = isomorphism We classify models by using invariants (properties of models that are preserved by isomorphism). –automorphism groups, endomorphism semigroups Classes of activities and objects are specified using these invariants. Preserving semantics is equivalent to preserving models of the axioms. – preserving models = isomorphism We classify models by using invariants (properties of models that are preserved by isomorphism). –automorphism groups, endomorphism semigroups Classes of activities and objects are specified using these invariants.

Semantic Translation Translation definitions specify the mappings between PSL and application ontologies. Example: The ilcActivity concept in ILOG Schedule maps to the activity concept in PSL only if the activity is either primitive or its nondeterminism arises only from resource selection. (forall (?a) (iff (ilcActivity ?a) (and(activity ?a) (or (nondet_res_activity ?a) (primitive ?a)))))

Twenty Questions How can we generate translation definitions? Each invariant from the classification of models corresponds to a different question. Any particular activity or object will have a unique value for the invariant. Each possible answer to a question corresponds to a different value for the invariant. How can we generate translation definitions? Each invariant from the classification of models corresponds to a different question. Any particular activity or object will have a unique value for the invariant. Each possible answer to a question corresponds to a different value for the invariant.

Process Descriptions If we shared an ontology of algebraic fields, we would not share arbitrary sentences; rather, we would share polynomials. Within PSL, process descriptions are boolean combinations of definable types realized in some model of the ontology. Example: precondition axioms are types for markov_precond activities If we shared an ontology of algebraic fields, we would not share arbitrary sentences; rather, we would share polynomials. Within PSL, process descriptions are boolean combinations of definable types realized in some model of the ontology. Example: precondition axioms are types for markov_precond activities

Major Project Milestones April 2000: PSL accepted as a New Work Item ISO within ISO SC4/SC5 October 2001: ISO passed CD ballot June 2002: ISO (Outer Core) submitted for CD ballot. September 2002: PSL 2.0 released (including grammars for process descriptions) November 2002: ISO (PSL-Core) passed CD ballot April 2000: PSL accepted as a New Work Item ISO within ISO SC4/SC5 October 2001: ISO passed CD ballot June 2002: ISO (Outer Core) submitted for CD ballot. September 2002: PSL 2.0 released (including grammars for process descriptions) November 2002: ISO (PSL-Core) passed CD ballot

Discussion Do we want an ontology of services or a language for building service ontologies? What are the scope and applications of a service ontology? What is the language for the ontology? –What is the relationship between this ontology and other standardization efforts? How heavy does the semantic machinery need to be? Do we want an ontology of services or a language for building service ontologies? What are the scope and applications of a service ontology? What is the language for the ontology? –What is the relationship between this ontology and other standardization efforts? How heavy does the semantic machinery need to be?

Further Questions? Michael Gruninger (301) Michael Gruninger (301)