Canadian Semantic Web: Technologies and Applications

by Weichang Du (Editor), Faezeh Ensan (Editor)

Overview

The emergence of Web technologies for the distribution of an immense amount of data and knowledge has given rise to the need for supportive frameworks for kno- edge management. Semantic Web technologies aim at providing shared semantic spaces for Web contents, such that people, applications and communities can use a common platform to share information. Canadian Semantic Web: Technologies and Applications aims at contributing to the advancement of the Semantic Web by providing the most recent significant - search on Semantic Web theory, techniques and applications in academia, industry and government in Canada and all over the world. It also enlightens possible - mantic Web research directions in future by reporting some works in-progress that presenton-goingresearchonprinciplesandapplicationsof theSemanticWeb,while their implementation or deployment may have not been completed. This book consists of ten chapters. The chapters are extended versions of a - lected set of papers from the second Canadian Semantic Web Working Symposium (CSWWS 2009) and the twenty-first international Conference on Software En- neering and Knowledge Engineering (SEKE 2009). CSWWS 2009 was held in Kelowna, British Columbia in May 2009. Since many of the challenging aspects of the research problems tackled in the Semantic Web area fall in the realm of Ar-—cial Intelligence or employ of AI techniques, CSWWS 2009 was organized in - nd sociation with the 22 Canadian Conference on Artificial Intelligence.

Product Details

ISBN-13:	9781441973344
Publisher:	Springer US
Publication date:	09/09/2010
Edition description:	2010
Pages:	217
Product dimensions:	6.10(w) x 9.25(h) x 0.02(d)

Table of Contents

1 Incremental Query Rewriting with Resolution Alexandre Riazanov Marcelo A. T. Aragão 1

1.1 Introduction 1

1.1.1 Settings and motivation 1

1.1.2 Outline of the proposed method 4

1.2 Informal method description 5

1.3 Soundness and completeness of schematic answer computation 10

1.4 Recording literals as search space pruning constraints 14

1.5 SQL generation 16

1.6 Implementation and experiments 17

1.7 A note on indexing Semantic Web documents with data abstractions 20

1.8 Related work 21

1.9 Summary and future work 23

References 25

2 Knowledge Representation and Reasoning in Norm-Parameterized Fuzzy Description Logics Jidi Zhao Harold Boley 27

2.1 Introduction 27

2.2 Preliminaries 31

2.3 Fuzzy Set Theory and Fuzzy Logic 32

2.4 Fuzzy Description Logic 34

2.4.1 Syntax of fALCN 35

2.4.2 Semantics of fALCN 35

2.4.3 Knowledge Bases in fALCN 38

2.5 Reasoning Tasks 39

2.6 GCI, NNF, and ABox Augmentation 41

2.7 Reasoning Procedure 43

2.8 Soundness, Completeness and Termination of the Reasoning Procedure for fALCN 45

2.9 Conclusion and Future Work 51

References 52

3 A Generic Evaluation Model for Semantic Web Services Omair Shafiq 55

3.1 Introduction 55

3.2 Performance Engineering for Component- and Service-oriented Systems 57

3.3 Requirements for a Generic Evaluation Model 58

3.3.1 Openness 58

3.3.2 Tool Independent 59

3.3.3 Conciseness 59

3.3.4 Preciseness 59

3.3.5 Completeness 59

3.3.6 Based on Classical Problems 60

3.3.7 Different Complexity Levels 60

3.3.8 Common Benchmarking 60

3.3.9 Flexibility to Perform Remote Evaluation 61

3.4 A Generic Evaluation Model for Semantic Web Services 61

3.4.1 Semantic Web Services Execution Lifecycle 62

3.4.2 Critical Evaluation Factors 64

3.5 Using the Evaluation Model for Semantic Web Services based on TSC 69

3.5.1 Comparing Resource Availability 69

3.5.2 Analyzing Performance on Concurrent Execution of Goals 70

3.5.3 Comparing Communication Overhead 70

3.5.4 Communication Overhead vs. Time Saved in Multiple Goal Execution 70

3.5.5 Comparing Time Taken in Distributed Service Execution 71

3.5.6 Comparing Time Saved by Applications while Executing a Goal 71

3.5.7 Comparing Time Saved in Resource Retrieval by WSMX 72

3.6 Related Work 72

3.6.1 Semantic Web Challenge 72

3.6.2 Semantic Web Services Challenge 73

3.6.3 Semantic Service Selection (S3) 73

3.6.4 IEEE Web Services Challenge 73

3.6.5 SEALS Evaluation Campaigns 74

3.6.6 STI International Test Beds and Challenges Service 74

3.6.7 International Rules Challenge at RuleML 75

3.7 Conclusions and Future Work 75

References 76

4 A Modular Approach to Scalable Ontology Development Faezeh Ensan Weichang Du 79

4.1 Introduction 79

4.2 Interface-Based Modular Ontologies 82

4.2.1 The Formalism 82

4.2.2 IBF: Scalability and Reasoning Performance 83

4.3 OWL Extension and Tool Support for the Interface-Based Modular Ontology Formalism 83

4.4 Evaluating IBF Modular Ontologies 89

4.4.1 cohesion 89

4.4.2 coupling 91

4.4.3 Knowledge Encapsulation 94

4.5 Case Studies 94

4.5.1 IBF Modular Ontologies 95

4.5.2 IBF Ontologies Analysis 97

4.6 Related Work 99

4.7 Conclusion 100

References 101

4.8 Appendix 103

5 Corporate Semantic Web: Towards the Deployment of Semantic Technologies in Enterprises Adrian Paschke Gökhan Coskun Ralf Heese Markus Luczak-Rösch Radoslaw Oldakowski Ralph Schäfermeier Olga Streibel 105

5.1 Introduction 105

5.2 Application Domains for a Corporate Semantic Web 106

5.3 Gaps 108

5.4 Corporate Semantic Web 109

5.5 Corporate Ontology Engineering 111

5.5.1 Modularization and Integration Dimensions of COLM 112

5.5.2 Versioning Dimensions of COLM 114

5.6 Corporate Semantic Collaboration 116

5.6.1 Editor Functionalities 117

5.6.2 User Groups 118

5.6.3 Design of the Light-weight Ontology Editor 119

5.7 Corporate Semantic Search 121

5.7.1 Search in Non-Semantic Data 122

5.7.2 Semantic Search Personalization 125

5.8 Conclusion and Outlook 130

References 130

6 Semantic Service Matchmaking in the ATM Domain Considering Infrastructure Capability Constraints Thomas Moser Richard Mordinyi Wikan Danar Sunindyo Stefan Biffl 133

6.1 Introduction 133

6.2 Related Work 136

6.2.1 Technical Integration 136

6.2.2 Semantic Integration with Semantic Web Services 138

6.2.3 Service Matchmaking Approaches 142

6.3 Research Issues 143

6.4 ATM Scenario Description 144

6.5 Semantic Service Matchmaking Approach 147

6.5.1 Identification of Possible Collaboration Candidate Sets 147

6.5.2 Validity-Check and Optimization of Collaborations 149

6.6 Case Study 150

6.6.1 Discussion 151

6.7 Conclusion 153

References 155

7 Developing Knowledge Representation in Emergency Medical Assistance by Using Semantic Web Techniques Heloise Manica Cristiano C. Rocha José Leomar Todesco M.A.R. Dantas 159

7.1 Introduction 159

7.2 Ontology and Mobile Devices Background 160

7.3 Proposed Approach 162

7.3.1 Ontology Development 163

7.3.2 Determining the Ontology Domain 164

7.3.3 Enumerating Important Terms, Classes and the Class Hierarchy 165

7.3.4 Defining Properties and Restrictions of Classes 166

7.3.5 Creating Instances and New Terms Extraction 166

7.3.6 Semantic Cache 170

7.4 Experimental Environment and Results 171

7.5 Conclusions and Future Work 171

References 173

8 Semantically Enriching the Search System of a Music Digital Library Paloma de Juan Carlos.Iglesias 175

8.1 Introduction 175

8.2 Research Context 177

8.2.1 Previous Work 177

8.2.2 Cantiga Project 177

8.3 MagisterMusicae Search System 178

8.4 Improving Searchability 179

8.4.1 Applying Semantic Web Technologies 179

8.4.2 Linking the Ontology with External Data Sources 185

8.4.3 Alternative Search Paradigms 187

8.5 Cantiga Semantic Search System 188

8.5.1 Details on the implementation 189

8.6 Evaluation 190

8.7 Related Work 192

8.8 Conclusions and Future Work 193

References 193

9 Application of an Intelligent System Framework and the Semantic Web for the CO₂ Capture Process Chuansan Luo Qing Zhou Christine W. Chan 195

9.1 Introduction 195

9.2 Backgroundt 196

9.2.1 Application Problem Domain 196

9.2.2 Ontology and Semantic Web 196

9.3 Knowledge Modeling and Ontology Construction 197

9.3.1 Ontology Design 197

9.3.2 Ontology Management 199

9.4 Intelligent System Framework 200

9.5 Application of the Semantic Knowledge A Web-based Expert System 202

9.6 Conclusion and Future Work 203

References 205

10 Information Pre-Processing using Domain Meta-Ontology and Rule Learning System Girish R Ranganathan Yevgen Biletskiy 207

10.1 Introduction 208

10.2 The domain mela-ontology 210

10.3 The system for semi-automatic population of domain mela-ontology 213

10.4 Details of the Rule Learning System flow 214

References 216