| Preface | 5 |
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| Organization | 7 |
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| Table of Contents | 13 |
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| Invited Papers | 17 |
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| P2P Semantic Mediation of Web Sources | 18 |
| Introduction | 18 |
| XML Data Mediation | 19 |
| Basics and Backgrounds | 19 |
| Overview of the XLive Mediator | 20 |
| P2P Data Systems | 21 |
| Basic P2P Architectures | 22 |
| Structural Routing | 23 |
| Semantic Routing | 23 |
| Pathfinder P2P Mediator | 24 |
| Objectives and Architecture | 24 |
| P2P Source Discovery | 26 |
| Query Execution | 27 |
| XML TE | 27 |
| The Semantic Layer | 29 |
| Conclusion | 30 |
| References | 30 |
| Reflective Community Information Systems | 32 |
| Internet Communities and Social Software | 32 |
| ATLAS: Metadata and Reflective Information Systems | 34 |
| Tools for Modeling and Analysis | 37 |
| Application Experiences | 39 |
| Summary and Outlook | 41 |
| References | 42 |
| Data Exchange Issues in Peer-to-Peer Database Systems | 44 |
| Introduction | 44 |
| Related Work | 47 |
| Main Issues | 48 |
| Evading Successive Query Rewriting | 49 |
| Conclusions and Future Work | 51 |
| References | 52 |
| On Enhancing Query Optimization in the Oracle Database System by Utilizing Attribute Cardinality Maps | 53 |
| Introduction | 53 |
| Contributions of This Paper | 55 |
| Basic Structure of a Script | 55 |
| Histogram Methods | 55 |
| QEP Determinations in ORACLE | 67 |
| Integration of the Methods into Oracle | 68 |
| The Core Architecture of Our Implementation | 68 |
| Selectivity Computation for Queries | 70 |
| Experimental Results | 70 |
| Test Data Sets | 70 |
| Sample Queries | 71 |
| Accuracy of the Error Estimates | 72 |
| Comparing the BT-ACM and Equi-depth for Uniform Distributions | 74 |
| QEP Selection Comparison | 74 |
| Example 1 | 75 |
| Example 2 | 76 |
| Conclusions | 78 |
| Part I Databases and Information Systems Integration | 88 |
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| Improvement of Software Development Processes, Balancing Internal and External Organizational Aspects | 90 |
| Introduction | 90 |
| Spi and the Necessity of Taking Both Internal and External Organisational Factors as Starting Point | 91 |
| Measuring Entropy | 93 |
| Entropy and Its Relations to Complexity and Dynamics | 93 |
| Entropy and Its Relations with Business System Aspects | 94 |
| Results of the Research: Space for Improvement for Software Development Organisations | 96 |
| Experience with Process Improvement | 96 |
| Positioning Organisations on the Basis of Their Entropy Scores | 97 |
| Conclusions | 99 |
| Measuring Enterprise Resource Planning (ERP) Systems Success: A Structural Equation Modeling Approach | 101 |
| Introduction | 101 |
| Background Information | 103 |
| Methodology | 105 |
| Result | 105 |
| Instrument Development and Validity | 106 |
| Data Analysis | 106 |
| Additivity of the ERP Systems Success Dimensions | 106 |
| Alternative Models | 108 |
| Discussions and Conclusion | 109 |
| References | 110 |
| Toward Data Compliance in Vaccine Industry: Interoperability to Align Business and Information Systems | 113 |
| Introduction | 113 |
| The Vaccine Industry | 114 |
| The Vaccine Supply Chain | 114 |
| The Vaccine Product | 115 |
| Vaccine Data Specifications | 116 |
| Interoperability in Vaccine Industry | 118 |
| The Interoperability Framework | 118 |
| General Requirement for Interoperability | 119 |
| Interoperability for Production Data Compliance | 119 |
| From MA to ERP | 119 |
| Type of Data to Be Translated | 120 |
| Rules Definition | 121 |
| Case Study | 123 |
| The Compliance Scenario | 123 |
| Validate Data in Sap | 124 |
| Conclusion | 125 |
| References | 126 |
| Evaluating Server Capacity for Streaming Media Services | 127 |
| Introduction | 127 |
| Methodology | 129 |
| Workload Selection | 129 |
| Server Capacity Decision | 130 |
| Data Calibration | 133 |
| Evaluation Results | 135 |
| Experimental Setup | 135 |
| Maximum Server Capacity | 136 |
| Server-Side Observations | 138 |
| Client-Side Observations | 141 |
| Prediction Model | 143 |
| Related Work | 144 |
| Conclusions | 145 |
| Part II Artificial Intelligence and Decision Support Systems | 148 |
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| On Processing Temporal Observations in Monitoring of Discrete-Event Systems | 150 |
| Introduction | 150 |
| Application Domain | 151 |
| Temporal Observations | 152 |
| Indexing Observations | 154 |
| Incremental Indexing | 155 |
| Discussion | 158 |
| Conclusion | 159 |
| Towards a Fuzzy Ontology Definition and a Fuzzy Extension of an Ontology Editor | 162 |
| Introduction | 162 |
| Definition and Use of a Fuzzy Ontology | 163 |
| Defining a Fuzzy Value | 163 |
| Updating a Fuzzy Value | 165 |
| An Example of Application: Extending Queries | 167 |
| Adding Fuzziness in KAON | 168 |
| Ontologies in KAON | 169 |
| Fuzzy Ontologies in KAON | 170 |
| Fuzzy OWL | 170 |
| Conclusions | 171 |
| References | 171 |
| Retrieval of Collaborative Filtering Nearest Neighbors in a Content-Addressable Space | 174 |
| Introduction | 174 |
| Collaborative
|