Semantic Technologies for E-Government (eBook)

Dr. Tomas Vitvar is a senior researcher with the Distributed and Parallel Systems group at the University of Innsbruck in Austria. He has over ten years of industrial and research experience gained while working as a software developer, IT architect, systems analyst, researcher and a lecturer. His professional interests are in distributed systems and applications including service-oriented computing, web services and enterprise computing.Dr. Vassilios Peristeras is a research fellow and adjunct lecturer in the Digital Enterprise Research Institute at the National University of Ireland, Galway. His research interests include eGovernment and e-participation, collaborative work environments, social software, and the Semantic Web. Dr. Konstantinos A. Tarabanis is a professor at the Department of Business Administration of the University of Macedonia, Greece. He was Research Staff Member at the IBM T.J. Watson Research Center where he worked on e-manufacturing techniques. His current research interests include conceptual modeling of information systems, service models and architectures, as well as the domains of e-government, e-learning, e-participation and e-business. He has received best paper awards from the European Conference on Information Systems for his work in e-government and from the International Academy of e-business for his work in e-business.

Foreword 6
Acknowlegements 7
Contents 8
Contributors 10
Semantic Technologies for E-Government: An Overview 14
1 E-Government: A Suitable Application Domain for Semantic Technologies 15
2 Difficulties in Applying Semantic Technologies in E- Government 16
3 Concepts and Technologies 17
3.1 Semantic Web 17
3.2 Ontology and Ontology Languages 18
3.3 Ontology Mediation 20
3.4 Semantic and Non-Semantic Descriptions 20
3.5 Semantic Annotations 21
3.6 Service Oriented Architecture 22
3.7 Semantic Web Services 22
3.8 Service Modeling Approaches 25
3.9 Web 2.0 26
3.10 Standardization 26
4 Organization of the Book 27
4.1 Part I: Architectures and Process Integration 27
4.2 Part II: Ontologies and Interoperability 29
4.3 Part III: Portals and User Interaction 31
5 Further Research 33
References 34
Part I Architectures and Process Integration 36
Pan-European E-Government Services Architecture 37
1 Introduction 37
2 Conceptual Architecture 38
2.1 Governing Principles 38
2.2 Stakeholders Layer 40
2.3 Problem-Solving Layer 41
2.4 Service Requester’s Layer 42
2.5 Middleware Layer 42
2.6 Service Providers Layer 44
3 Architecture Services 45
3.1 Middleware Services 45
3.2 PA Services 46
4 Detail Architecture 47
4.1 Technology 47
4.2 Member State Portal 50
4.3 Management Suite 50
4.4 WSMO-PA 51
4.5 Member State Middleware 53
5 Conclusion 57
References 58
Employing Semantic Technologies for the Orchestration of Government Services 59
1 Introduction 59
2 Problem Definition 61
3 Conceptual Modelling of Integrated Government Services 62
3.1 Conceptual Model 63
3.2 Ontology Design 64
4 Access-eGov System 66
4.1 Basic System Modules and Components: Discovery of Services 67
4.2 Orchestration and Choreography Process Model 68
4.3 Composition and Execution Environment 71
4.4 Interface Components and User-Side Tools 72
5 Application Examples 73
5.1 Example on the Composition and Execution of Services 74
5.2 Pilot Applications 79
6 Related Research 80
7 Conclusion 83
References 84
The Modelling of Knowledge-Intensive Processes Using Semantics 87
1 Motivation 87
2 The Three Phases of the Knowledge-Intensive Business Process Modelling Approach 89
2.1 Phase 1: The Business Model 90
2.2 Phase 2: The Interchange Model 94
2.3 Phase 3: The Execution Model 98
3 Evaluation 102
4 Conclusion 108
References 109
E-Government Goes Semantic Web: How Administrations Can Transform Their Information Processes 111
1 Introduction 111
2 Semantic-Based Information Processing in E-Government 112
2.1 From Strategy to Implementation: Semantic Interoperability 113
2.2 Upgrading Information Processes in Schleswig-Holstein 117
3 Administrations as Key Transformers: Challenges and Motivators 120
3.1 Challenges 120
3.2 Motivators 122
3.3 Strategic Decision in Schleswig-Holstein 122
4 Transitioning to the Semantic Web Step by Step 123
4.1 Identifying Informational Needs of Users and Required Information Quality 124
4.2 Establish and Maintain a Common Conceptual Ground 125
4.3 Restructuring and Annotating a Wide Range of Services and Web Resources 127
4.4 Processing Information with Semantic Technology 128
4.5 Build and Maintain IT Infrastructure 130
4.6 Creating Take-up 131
4.7 Finding Partners and Building Networks 133
5 Conclusion: Lessons Learned and Future Work 134
References 136
Part II Ontologies and Interoperability 138
A Semantic Cooperation and Interoperability Platform for the European Chambers of Commerce 139
1 Introduction 139
2 The LD-CAST Phased Semantic Approach 142
2.1 Phase 1: Application Resources Set Up 142
2.2 Phase 2: Development of Semantic Contents 142
2.3 Phase 3: Business Process Workflow Setup 144
2.4 Phase 4: Business Process Workflow Execution 145
2.5 Summarizing the Role of the LD-CAST Ontology 146
3 OFV-Based Annotation in LD-CAST 148
4 The Weighted Reference Ontology 150
5 Semantic Search and Discovery in LD-CAST 152
5.1 The Semantic Matchmaking Mechanism 152
5.2 The Semantic Matchmaking Algorithm 153
( 154
6 Related Works 156
6.1 A Semantic Approach to Web Services and Business Processes 156
6.2 Similarity Searching Algorithms 157
7 Conclusions 158
References 159
SEEMP: A Networked Marketplace for Employment Services 160
1 Introduction 160
2 Employment Market Vision 2.1 Employment Market Need 161
2.2 Business Vision: Employment Mediation Marketplace 163
2.3 Actors in EMM 164
2.4 Goods of EMM 165
2.5 Benefits and Impacts of EMM 168
3 SEEMP Technological Approach 169
3.1 Minimal Shared Commitment 171
3.2 Best Practice in the SEEMP Project 173
3.3 Technological Employment Marketplace Platform 176
3.4 Layers and Services Level 176
3.5 The Connector Level 179
4 Use Case 183
5 Discussion and Concluding Remarks 187
5.1 Alternative Architecture Paradigms 187
5.2 Interoperability 188
5.3 Best Practice 189
5.4 Main Achievements 190
References 191
Semantic Repositories for eGovernment Initiatives: Integrating Knowledge and Services 193
1 Introduction 193
2 Background and Motivations: ICT to Support eGovernment Programs 194
3 Repository of Conceptual Schema of Public Administration Information Systems: Structure and Exploitation 196
3.1 Governance of Data for eGovernment Information Integration Initiatives 196
3.2 The Structure of a Repository 197
3.3 Designing and Maintaining the Repository 198
3.4 Semi-Automatic Data Reverse Engineering with the Repository 200
4 A Semantic Repository of Services to Support Service Discovery and Selection in G2B 202
4.1 The IPAS Ontology 204
4.2 The IPAS Application Framework for Service Selection 206
5 Related Work 209
6 Integration of the Two Repositories: Conclusions and Future Perspectives 211
References 213
Toward an E-Government Semantic Platform 216
1 Introduction 216
2 Semantics for E-Government 218
3 Engineering Process of the Core Ontology 219
4 Structure of the Core Ontology 221
5 Indexing and Searching Tools 223
6 Semantic Web Services for E-Government 225
7 An Application Framework for Semantic Web Services 226
8 E-Government Applications 229
9 A Real-World Scenario 232
10 Use Case Description 233
11 Use Case Analysis 234
12 Application Description 235
13 Evaluation 237
14 Conclusions 239
References 239
Part III Portals and User Interaction 242
Semantic-Based Knowledge Management in E- Government: Modeling Attention for Proactive Information Delivery 243
1 Introduction 243
2 Conceptual and Empirical Background 2.1 The Knowledge Landscape in Public Administrations 245
2.2 Public Administrations in Need for KM 246
2.3 Motivations for Technical Development 246
3 Proactive Information Delivery: A Role for Ontologies 248
4 Modeling Attention: A New Challenge for Knowledge Management 249
5 The SAKE System 251
5.1 Attention Model 251
6 The SAKE Enterprise Attention Management System 252
6.1 Information Ontology 254
6.2 Log Ontology 255
6.3 Change Notification System 257
6.4 Context Observer 258
6.5 Preference Editor 259
6.6 Reasoner 261
7 Technical Implementation 262
8 Related Work 263
9 Conclusion 265
References 265
Personalization in E-Government: An Approach that Combines Semantics and Web 2.0 267
1 Introduction 267
2 Motivating Example 269
3 Logical System Architecture: The Adaptation Loop 271
4 Ontology-Based Adaptation of Public Services 272
4.1 Advantages of Using Ontologies for Adaptation 272
4.2 Ontology-Based Model of Adaptive Portals 274
5 Architecture of Adaptive Portals for E-Government 277
5.1 Design-Time Architecture 277
5.2 Run-Time Architecture: A Client-Side Intelligent Adaptation Engine 278
6 Evaluation 280
7 Hypotheses 280
7.1 Main Hypothesis 280
7.2 Subhypotheses 280
8 Planning 281
9 Design 282
10 Architecture and Implementation 284
10.1 The Adaptive Portal 285
10.2 Test of the Evaluation Portal 285
11 Execution and Test Results 285
11.1 Demographics 286
11.2 Quantitative Test Results 286
11.3 Qualitative Test Results 287
12 Discussion 288
13 Related Work 288
14 Conclusion and Future Work 289
References 290
A Semantically Enabled Portal for Facilitating the Public Service Provision 292
1 Introduction 292
2 Background Technologies 294
2.1 Government Enterprise Architecture Public Administration Service Model 294
2.2 The Web Service Modeling Ontology 296
2.3 A Formal Description of PA Services: The WSMO-PA Specification 296
2.4 The Web Service Modeling Language 297
3 Organizing Public Service Information as Ontologies 298
3.1 The Meta-Ontology for Goal Tree Ontologies 299
3.2 The Goal Tree Ontology 301
4 Actors and Functionalities 304
4.1 Find Public Service 305
4.2 Invoke Public Service 306
4.3 Manage Goal Tree Ontologies 306
5 SemanticGov Portal Architecture 306
5.1 The PA Client subsystem 307
5.2 The Administrative Subsystem 313
5.3 The Common Repositories 315
6 Conclusions 316
References 318
Index 320