International Semantic Web Doctoral Symposium

Research Topic:Representing Discrete-Event Simulation Process-Interaction

Models using the Web Ontology Language - OWL

November 7, 2005

Lee W. LacyPhD Candidate

University of Central Florida

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PIMODES Research Overview

• Discrete-event simulation models support operations research and other applications

• These models have historically been represented in vendor-specific file formats that have made sharing/interchange difficult

• Research is being performed to develop an OWL ontology that will provide a neutral interchange description of these types of models.

• The ontology is being scoped to a particular type of discrete event simulation model descriptions – those that adhere to the process-interaction world view

• The interchange of simulation models using the ontology will be demonstrated using web-based software

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Presentation Outline

• Purpose Description

• Goal Statement

• Methodology

• Evaluation

• Summary

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Purpose Description

• Simulation Model Interchange Challenges

• Scoping the Problem

• Subject Domain

• Benefits of Interchange

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Why Interchange Models?

• Leverage investment in model development through reuse– Higher quality through reuse of validated models

– Speed development lifecycle

– Reduce development costs

• Enable competition of model development environments and compliant execution engines– Potential software manufacturer push-back if not presented

correctly

– Need to sell the HTML and XML business models

• Shift model development emphasis from programming to model quality

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Scoping the Proposed Research

• Simulation data interchange topic broad

• Various types of simulation data

• Emphasis shifting from code to data

• Simulation models represent one type of data in newer “data-driven” systems

• Model is problem-specific while execution engine is problem-independent

• Discrete-event simulations represent one type of simulation

• Further scoped by “world view”

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Subject Domain

described by

ModelingLanguage

Simulation Software

System Model

serialized by

ModelingFormalism /

Representation

System-Specific

System-Independent

encoded using

typically tightly coupled

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Benefits of Model Interchange

• Better– Reuse of validated models

• Faster– Quicker to create new models by leveraging existing models

• Cheaper– Lower cost due to reuse instead of creation

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Goal Statement

• Develop an ontology to support Discrete Event simulation model interchange

• Ontology becomes a “de facto” language

• New ontology/language harmonizes the most important aspects of legacy languages

• Legacy models can then be converted to/from the new “lingua franca” – enabling interchange

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Methodology

• Use of OWL Ontologies

• Research Activities

• Research Plan

• Feedback Opportunities

• Anticipated Results

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Simulation Ontology Representations

• Proposed by Lacy (2004) and Miller & Fishwick (2004)

• Provides advantages over traditional (e.g., XML) approaches

• Requires the development of a meta-model

• Existing modeling languages have implicit ontologies

• New explicit ontologies in effect describes a new modeling language

• Mappings required from legacy languages to the new ontology

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Web Ontology Language - OWL

• OWL became a World Wide Web Consortium (W3C) Standard in February 2004

• OWL will be used to define a Process-Interaction Modeling Ontology for Discrete-Event Simulations (PIMODES)

• Compliant instance files are represented using RDF/XML

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OWL’s Layered Architecture

Applications

Ontology Languages (OWL Full,OWL DL, and OWL Lite)

RDF and RDF/XML

XML and XMLS Datatypes

URIs and Namespaces

RDF Schema Individuals

Implementation Layer

Logical Layer

Ontological PrimitiveLayer

Basic RelationalLanguage Layer

Transport/Syntax Layer

Symbol/Reference Layer

}}}}}}

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Research Plan

A0

Perform DEVSOntologyResearch

Authoritative Data Sources

UCFGuidelines /Procedures

Plan ofStudy

Dissertation

Software Tools

Research Concept Presentation

ActivityInput

Control / Constraint

Output

Mechanism

Legend

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A0 View

A1

Plan Research

A2

Perform LiteratureSearch

A3

Develop DEVSOntology

A4

DemonstrateOntology Use

A5

Document andDefend

Research Plan

DistilledADSs /Notes

DEVSOntology

Tools

Dissertation

Authoritative Data Sources

Background Section,Reference Section

OWL LanguageStandards

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A2 – Literature Search (¶2) Activities

• Formalize domain semantics (¶2.1)

• Survey existing discrete-event process-interaction (¶2.2)– Software packages (¶2.2.2)

– Modeling languages (¶2.2.3)

– Formalisms/Representation methods (¶2.2.4)

• Review related simulation information interchange research (¶2.3)

• Describe Semantic Web technology (¶2.4)

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Evaluation

• Develop sample model in ProcessModel and Arena

• Convert legacy model representations to DEPIM

• Convert DEPIM representation to legacy formats

• Compare converted models to original models

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Demonstration Data Flow

compliant withRDF

RDF

PIMODESOntology(OWL)

RDF

Arena Software

ProcessModel

AnyLogic

Commercial SoftwareApplications

Legacy ArenaModel

Legacy ProcessModelModel

Legacy AnyLogicModel

Proprietary Formats

Conversion Routines

RDF/XML InstanceData

Converted ArenaModel

ConvertedProcessModel

Model

ConvertedAnyLogic Model

compliant with

compliant with

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Summary

• Simulation data is interchanged in a variety of ways

• Interchange is best performed with open standards

• OWL can be used to define an ontology for Discrete-Event Process-Interaction models

• Use of such an ontology can be demonstrated by converting legacy simulation model formats