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Modeling and Simulation-Based Data Engineering -  Phillip E Hammonds,  Bernard P. Zeigler

Modeling and Simulation-Based Data Engineering (eBook)

Introducing Pragmatics into Ontologies for Net-Centric Information Exchange
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2007 | 1. Auflage
448 Seiten
Elsevier Science (Verlag)
978-0-08-055054-1 (ISBN)
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Data Engineering has become a necessary and critical activity for business, engineering, and scientific organizations as the move to service oriented architecture and web services moves into full swing. Notably, the US Department of Defense is mandating that all of its agencies and contractors assume a defining presence on the Net-centric Global Information Grid. This book provides the first practical approach to data engineering and modeling, which supports interoperabililty with consumers of the data in a service- oriented architectures (SOAs). Although XML (eXtensible Modeling Language) is the lingua franca for such interoperability, it is not sufficient on its own. The approach in this book addresses critical objectives such as creating a single representation for multiple applications, designing models capable of supporting dynamic processes, and harmonizing legacy data models for web-based co-existence. The approach is based on the System Entity Structure (SES) which is a well-defined structure, methodology, and practical tool with all of the functionality of UML (Unified Modeling Language) and few of the drawbacks. The SES originated in the formal representation of hierarchical simulation models. So it provides an axiomatic formalism that enables automating the development of XML dtds and schemas, composition and decomposition of large data models, and analysis of commonality among structures.

Zeigler and Hammond include a range of features to benefit their readers. Natural language, graphical and XML forms of SES specification are employed to allow mapping of legacy meta-data. Real world examples and case studies provide insight into data engineering and test evaluation in various application domains. Comparative information is provided on concepts of ontologies, modeling and simulation, introductory linguistic background, and support options enable programmers to work with advanced tools in the area. The website of the Arizona Center for Integrative Modeling and Simulation, co-founded by Zeigler in 2001, provides links to downloadable software to accompany the book.

* The only practical guide to integrating XML and web services in data engineering
* Introduces linguistic levels of interoperability for effective information exchange
* Covers the interoperability standards mandated by national and international agencies
* Complements Zeigler's classic THEORY OF MODELING AND SIMULATION
Data Engineering has become a necessary and critical activity for business, engineering, and scientific organizations as the move to service oriented architecture and web services moves into full swing. Notably, the US Department of Defense is mandating that all of its agencies and contractors assume a defining presence on the Net-centric Global Information Grid. This book provides the first practical approach to data engineering and modeling, which supports interoperabililty with consumers of the data in a service- oriented architectures (SOAs). Although XML (eXtensible Modeling Language) is the lingua franca for such interoperability, it is not sufficient on its own. The approach in this book addresses critical objectives such as creating a single representation for multiple applications, designing models capable of supporting dynamic processes, and harmonizing legacy data models for web-based co-existence. The approach is based on the System Entity Structure (SES) which is a well-defined structure, methodology, and practical tool with all of the functionality of UML (Unified Modeling Language) and few of the drawbacks. The SES originated in the formal representation of hierarchical simulation models. So it provides an axiomatic formalism that enables automating the development of XML dtds and schemas, composition and decomposition of large data models, and analysis of commonality among structures. Zeigler and Hammond include a range of features to benefit their readers. Natural language, graphical and XML forms of SES specification are employed to allow mapping of legacy meta-data. Real world examples and case studies provide insight into data engineering and test evaluation in various application domains. Comparative information is provided on concepts of ontologies, modeling and simulation, introductory linguistic background, and support options enable programmers to work with advanced tools in the area. The website of the Arizona Center for Integrative Modeling and Simulation, co-founded by Zeigler in 2001, provides links to downloadable software to accompany the book. - The only practical guide to integrating XML and web services in data engineering- Introduces linguistic levels of interoperability for effective information exchange- Covers the interoperability standards mandated by national and international agencies- Complements Zeigler's classic THEORY OF MODELING AND SIMULATION

Cover 1
Contents 8
Foreword 12
Part I: Foundations 16
Chapter 1: Ontologies and Information Exchange: A Pragmatic Framework 18
Ontology for Social Relations on an Island 19
Definition of Ontology 20
Ontology Summary: Prelude to the Framework in This Book 23
Pragmatics: The Information Exchange Framework 24
Summary 27
References 27
Chapter 2: Background: Syntax, Semantics, and Ontology Environments 28
Semantics: Testing Web Services 29
Syntax and XML 30
Semantics „ Ontologys Ability to Match Its Set of World Structures to the Pragmatic Frames It Supports 32
XML Schema: Strengths and Limitations 32
UML 37
UML and XML Combined: Strengths and Limitations 39
Open Knowledge Base Connectivity Ontology 40
Semantic Web Ontologies and Environments 43
Summary 44
References 45
Appendix A: Review of OKBC Knowledge Specification (based on13) 46
Chapter 3: Formulating Pragmatic Frames and Ontologies: Geospatial Sensor Data 50
Geospatial Imagery Sensors Background 52
Pragmatic Frame for Downstream Image Processing 56
Sensor Model 59
Pragmatic Frame Principles: Maxims for Effective Conversations 60
Summary 63
References 64
Part II: System Entity StructureConcepts and Operations 66
Chapter 4: Introduction to the System Entity Structure 68
Variables 69
Aspects 69
Specializations 71
Interaction between Aspects and Specializations 72
Interaction among Specializations 74
multiAspects 75
Variables and Range Specifications 78
Range Restrictions 79
Computed Values and Formulas 81
Summary 83
References 84
Chapter 5: System Entity Structure Axioms: Interpretations and Applications 86
Relational Specification of the SES 87
Application of Uniformity 91
Satisfaction of the Axioms 93
Unique Path Labeling 96
Pruning Process: Brief Introduction 97
System Entity Structure with multiAspects 97
Inheritance 99
Summary 102
Problems 103
References 103
Chapter 6: System Entity Structure: Computational Representations 105
Creating an Instance of Class sesRelation 106
Representing the SES as a DOM 109
Specifying the SES as an XML File 111
Creating a DOM from an SES XML File 113
Writing from a DOM for an SES into a DTD 113
Testing an SES for Validity 115
Schema Representation of SES 117
Schema Validation of SES 121
Natural Language Specification of an SES 122
Summary 122
References 123
Appendix A: Syntax for Natural Language Specification of an SES 123
Chapter 7: Mappings: Transformations and Restructurings 128
Tree Operations: Eliminating Specialization and Aspect Labels 129
Restructuring of multiAspects 132
Restructuring Variables and Specializations 136
Partitioning Continuous Ranges Using Specializations 138
Converting between Variables and Aspects 138
Increasing Specialization Specificity 140
Summary 141
Chapter 8: Pruned Entity Structures and XML Schema Instances 143
Pruned Entity Structures 145
Pruning an SES with multiAspects 150
Prunable Entity Structures 150
The conformsTo Relation 153
When Is Pruning Complete? 154
Pruning Using SES/JAVA Tools 156
Validation and Completion State of PES 159
Summary 160
Reference 160
Chapter 9: Constrained Pruning 161
Constraints on Specialization Selections 161
Rule-based Approach 162
Relation-based Approach 169
Implementation 172
Relation-based Pruning for multiAspects 175
Summary 180
References 180
Appendix A: Logical Formulation of Selection Rules 180
Appendix B: Theory Support for Relation-based Pruning 182
Chapter 10: Pruned Entity Structures: Data Extraction and Change-based Information Exchange 191
Extracting Data from Pruned Entity Structures 192
Using Context to Shorten Path Identifiers 194
Change-based Information Exchange 198
Summary 201
Reference 202
Appendix A: Top Ancestor as Context Information 202
Part III: Modeling and Simulationand Data Engineering 208
Chapter 11: Hierarchical Systems, Models, and Simulations: The SES Ontology 210
Why Hierarchical Structure? 211
Hierarchical Modular Simulation Models „ Universe of Discourse for the SES Ontology 212
The Levels of System Specifications 214
Dynamic Data Representations 216
Operations on Event Sets and DEVS Model Realizations 218
Constructing Hierarchical Event Sets 222
Summary 223
References 223
Chapter 12: Managing System Entity Structures: Composing Large Systems 225
Composing Hierarchical Systems and Models 229
Targeted Access to Substructures 232
Decomposition 233
Summary 233
Chapter 13: Harmonizing Data Representations and Ontologies within Pragmatic Frames 234
Harmonization: Pragmatic Equivalence 237
Harmonization of Data Formats 240
Need for More Structured Representation 242
Current Tools for Ontology Integration 243
Harmonization Supported by the SES 243
Measuring Commonality 246
Harmonization: Increasing Commonality Via Restructuring 247
Tracking Restructurings 251
Synchronizing Prunings from Harmonized SESs 252
Summary 254
References 255
Chapter 14: Geospatial Sensor Data: The Universal Phase History Data (UPHD) Standard 257
Background: Synthetic Aperture Radar Sensing 258
Goals for UPHD Standard Development 260
Universality and Scope of the UPHD Standard 262
Approach: Syntactic, Semantic, and Pragmatic 265
Relation to Systems Modeling and Simulation 266
Generic Formulation of an SAR System 266
Components of the SES 267
Wave Form Parameters (WF) 268
Wideband Vector Header Data (VH) 271
Spatial Data about the Platform/Vehicle (SV) 271
UPHD Global Range Definitions 277
Managing the UPHD Master and Its Components 279
Complexity Measures of the UPHD and Its Components 280
Summary 284
References 284
Appendix A: Abbreviations 284
Appendix B: UPHD Table of All Paths 285
Chapter 15: Processing Networks and Pragmatic Frames 288
Processing Network Pragmatics 289
Layered Processing Networks 292
Repository of Discoverable Data 299
Dynamically Evolving Processing Networks 300
Summary 301
References 302
Chapter 16: Dynamic Pragmatics: Issues and Methodology 303
Information Exchange between Humans, Systems, and Services 305
Static Pragmatic Frames 310
Managing Pragmatic Equivalence within the SES 316
Static Pragmatic Frame Analysis 318
Dynamic Pragmatics 318
How Pragmatics Enhances Semantics 321
Summary 323
References 324
Appendix A: Dynamic Harmonization Goal-seeking Control Theory Analogy 325
Appendix B: Pragmatic Frame Conjecture 325
Part IV: Testing in Net-CentricEnvironments 336
Chapter 17: Testing in a Net-Centric Environment: Technology Basis 338
Introducing Automation into Traditional Testing of Standards Conformance 339
Employing Agent-based Technology for Web-Services Testing 352
Summary 369
References 370
Appendix A: Infusion of Modeling and Simulation into Defense Acquisition 371
Appendix B: Opportunistic Message Tester 372
Chapter 18: Testing in a Net-Centric Environment: Multiple Levels 376
Simultaneous Testing at Multiple Levels 383
Integrated Architectures for System Development and Testing 387
Summary 397
References 398
Appendix A: Testing for Pruning Rule Satisfaction 400
Chapter 19: Bringing It All Together: Modeling and Simulation-based Data Engineering 403
Revisiting the SES Framework 405
Geographic Information Representation in UML and Encoding in XML 409
Web Ontology Language (OWL) 415
UML and Ontology Development 418
The SES Framework within the UML Context 419
Summary 427
Further Research and Development 427
References 427
Appendix A: Scalable Entity Structure Modeler (SESM) 428
Glossary 433
Index 438

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