| Foreword |
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xi | |
| Preface |
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xiii | |
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1 | (28) |
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1.1 Background and Motivations |
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1 | (7) |
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1.1.1 Web Service and Service-Oriented Architecture |
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1 | (3) |
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1.1.2 Workflow Technology |
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4 | (4) |
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1.2 Overview of Standards |
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8 | (14) |
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1.2.1 Web Service-Related Standards |
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8 | (11) |
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1.2.2 Workflow-Related Standards |
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19 | (3) |
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1.3 Workflow Design: State of the Art |
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22 | (5) |
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1.3.1 Automatic Service Composition |
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22 | (1) |
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1.3.2 Mediation-Aided Service Composition |
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23 | (1) |
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1.3.3 Verification of Service-Based Workflows |
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24 | (1) |
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1.3.4 Decentralized Execution of Workflows |
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25 | (1) |
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1.3.5 Scientific Workflow Systems |
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26 | (1) |
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27 | (2) |
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29 | (10) |
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29 | (3) |
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32 | (3) |
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35 | (4) |
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3 Data-Driven Service Composition |
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39 | (26) |
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40 | (5) |
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3.1.1 Domains and Data Relations |
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41 | (2) |
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3.1.2 Problem Formulation |
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43 | (2) |
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3.2 Data-Driven Composition Rules |
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45 | (3) |
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3.2.1 Sequential Composition Rule |
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46 | (1) |
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3.2.2 Parallel Composition Rule |
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46 | (1) |
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3.2.3 Choice Composition Rule |
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47 | (1) |
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3.3 Data-Driven Service Composition |
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48 | (7) |
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48 | (2) |
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3.3.2 Derive AWSP from Service Net |
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50 | (5) |
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3.4 Effectiveness and Efficiency of the Data-Driven Approach |
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55 | (2) |
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3.4.1 Solution Effectiveness |
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55 | (1) |
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3.4.2 Complexity Analysis |
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56 | (1) |
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57 | (3) |
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60 | (1) |
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61 | (1) |
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62 | (3) |
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4 Analysis and Composition of Partially-Compatible Web Services |
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65 | (34) |
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4.1 Problem Definition and Motivating Scenario |
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65 | (5) |
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4.1.1 A Motivating Scenario |
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68 | (2) |
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4.2 Petri Net Formalism for BPEL Service, Mediation, and Compatibility |
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70 | (8) |
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4.2.1 CPN Formalism for BPEL Process |
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70 | (3) |
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4.2.2 CPN Formalism for Service Composition |
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73 | (2) |
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4.2.3 Mediator and Mediation-Aided Service Composition |
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75 | (3) |
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4.3 Compatibility Analysis via Petri Net Models |
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78 | (10) |
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4.3.1 Transforming Abstract BPEL Process to SWF-net |
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79 | (1) |
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4.3.2 Specifying Data Mapping |
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80 | (1) |
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4.3.3 Mediator Existence Checking |
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81 | (4) |
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4.3.4 Proof of Theorem 4.1 |
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85 | (3) |
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4.4 Mediator Generation Approach |
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88 | (6) |
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88 | (2) |
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4.4.2 Guided Mediator Generation |
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90 | (4) |
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94 | (5) |
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4.5.1 Web Service Composition |
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94 | (1) |
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4.5.2 Business Process Integration |
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94 | (1) |
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4.5.3 Web Service Configuration |
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94 | (1) |
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4.5.4 Petri Net Model of BPEL Processes |
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94 | (1) |
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4.5.5 Component/Web Service Mediation |
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95 | (4) |
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5 Web Service Configuration with Multiple Quality-of-Service Attributes |
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99 | (28) |
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99 | (5) |
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5.2 Quality-of-Service Measurements |
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104 | (3) |
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104 | (1) |
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104 | (1) |
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105 | (2) |
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5.3 Assembly Petri Nets and Their Properties |
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107 | (7) |
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5.3.1 Assembly and Disassembly Petri Nets |
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107 | (3) |
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5.3.2 Definition of Incidence Matrix and State-Shift Equation |
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110 | (1) |
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5.3.3 Definition of Subgraphs and Solutions |
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111 | (3) |
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5.4 Optimal Web Service Configuration |
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114 | (7) |
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5.4.1 Web Service Configuration under Single QoS Objective |
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115 | (1) |
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5.4.2 Web Service Configuration under Multiple QoS Objectives |
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116 | (1) |
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5.4.3 Experiments and Performance Analysis |
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117 | (4) |
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121 | (2) |
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123 | (1) |
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124 | (3) |
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6 A Web Service-Based Public-Oriented Personalized Health Care Platform |
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127 | (34) |
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6.1 Background and Motivation |
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127 | (2) |
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129 | (8) |
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6.2.1 The System Architecture of Phisp |
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129 | (2) |
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6.2.2 Services Encapsulated in Phisp |
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131 | (2) |
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6.2.3 Composite Service Specifications |
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133 | (1) |
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6.2.4 User/Domain Preferences |
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134 | (3) |
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6.3 Web Service Composition with Branch Structures |
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137 | (16) |
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6.3.1 Basic Ideas and Concepts |
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137 | (2) |
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6.3.2 Service Composition Planner Supporting Branch Structures |
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139 | (9) |
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6.3.3 Illustrating Examples |
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148 | (5) |
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6.4 Web Service Composition with Parallel Structures |
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153 | (2) |
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6.5 Demonstrations and Results |
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155 | (4) |
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6.5.1 WSC Example in PHISP |
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155 | (3) |
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6.5.2 Implementation of PHISP |
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158 | (1) |
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159 | (2) |
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7 Scientific Workflows Enabling Web-Scale Collaboration |
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161 | (28) |
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7.1 Service-Oriented Infrastructure for Science |
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162 | (5) |
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7.1.1 Service-Oriented Scientific Exploration |
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162 | (4) |
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7.1.2 Case Study: The Cancer Grid (caGrid) |
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166 | (1) |
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7.2 Scientific Workflows in Service-Oriented Science |
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167 | (21) |
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7.2.1 Scientific Workflow: Old Wine in New Bottle? |
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167 | (7) |
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7.2.2 caGrid Workflow Toolkit |
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174 | (9) |
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7.2.3 Exemplary caGrid Workflows |
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183 | (5) |
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188 | (1) |
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8 Network Analysis and Reuse of Scientific Workflows |
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189 | (32) |
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8.1 Social Computing Meets Scientific Workflow |
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190 | (9) |
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8.1.1 Social Network Services for Scientists |
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191 | (6) |
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8.1.2 Related Research Work |
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197 | (2) |
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8.2 Network Analysis of myExperiment |
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199 | (8) |
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8.2.1 Network Model at a Glance |
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199 | (1) |
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200 | (5) |
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205 | (1) |
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8.2.4 Summary of Findings |
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206 | (1) |
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8.3 ServiceMap: Providing Map and GPS Assisting Service Composition in Bioinformatics |
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207 | (12) |
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207 | (2) |
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8.3.2 ServiceMap Approach |
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209 | (1) |
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8.3.3 What Do People Who Use These Services Also Use? |
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210 | (2) |
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8.3.4 What is an Operation Chain Between Services/Operations |
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212 | (6) |
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218 | (1) |
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219 | (2) |
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221 | (6) |
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9.1 Workflows in Hosting Platforms |
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222 | (1) |
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9.2 Workflows Empowered by Social Computing |
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223 | (1) |
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9.3 Workflows Meeting Big Data |
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224 | (1) |
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9.4 Emergency Workflow Management |
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225 | (2) |
| Abbreviations List |
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227 | (4) |
| References |
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231 | (16) |
| Index |
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247 | |