Semantic Annotation for Process Models: - Department of Computer ...

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100 CHAPTER 6. PRO-SEAT (PROCESS SEMANTIC ANNOTATION TOOL) Figure 6.9: Structure of process model fragment is given a lower weight for a subsumption relationship (σ = 0.8), and the meronym ("phase_of" for activity, "part_of" for artifact, "member_of" for actor-role) is given the lowest weight for a subset relationship (σ = 0.5). In the string match, an exact match gets higher weight than a sub-string match (τ = 1 for exact match, and τ = 0.5 for sub-string match). Weights are also different for each case. We set different weight parameters for four cases matching. Values of parameters can be set by users. For example, α is used as the weight for calculation results of ontology comparison in case A, and ε is for calculation results of ontology comparison in case C. Details of the algorithm are described in Appendix D. When matching a goal concept (g) with an activity (av) in models, all the four cases must be checked on g and av. The result of a match is a total weight by summing the calculation results from four cases. The higher total weight is, the better g matches av. 6.4 Functionality and User Interface The main functionalities of Pro-SEAT in this prototype version are as follows: profile annotation, meta-model annotation, model annotation, goal annotation and querybased model navigation. UI (User Interface) for each annotation phase has a similar layout, which is built as a template and instantiated for different annotation phases. Figure 6.10 shows main user interface components in the Pro-SEAT tool. A meta-model tree and a model tree are listed on the left side of the main frame. The meta-model and the model trees have the same hierarchical structure as the tree structure viewed from the Metis tool. The panel on the right side is for manipulating annotations and displaying results. If it is an ontology-based annotation, such as a meta-model, a model or a goal annotation, a reference ontology browser will be opened and embedded on the right annotation panel. A console is located at the bottom of the frame. Figure 6.10 is an instantiation of the user interface template for a metamodel annotation. Appendix E presents and visualizes the graphical user interfaces of
6.5. SUMMARY 101 Figure 6.10: Main components of the UI in Pro-SEAT Pro-SEAT for each annotation phase. In the current version of Pro-SEAT, a navigator UI provides the function of querybased model navigation (Figure 6.11). The process knowledge user can select a reference ontology concept as the query word and submit the query to the system. During the query, the system can make inference based on the ontology. Therefore, the system would return the model elements annotated with not only the given ontology concept but also the inferred concepts of the given ontology concept. Inferences concerned in a query includes semantic equivalence, subsumption and aggregation relationships between concepts. 6.5 Summary The proposed annotation approach could be realized through different tool implementations by various technologies. The prototype developed in this work shows one possible implementation. This annotation tool provides a way of annotating meta-models and model elements with OWL ontological concepts. The current version of the model annotation tool is mainly designed for interpreting models created by the Metis tool. It can be extended to import other models produced by different modeling tools. Because the tool integrates the Protégé-OWL API, it can load any OWL ontology created by Protégé.
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Yun Lin Semantic Annotation for Pro
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To MY BELOVED HUSBAND HAO DING AND
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ii The proposed approach has been i
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iv CONTENTS 3 State of the Art 31 3
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vi CONTENTS 7.5.2 Semantic reasonin
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viii CONTENTS H PSAM Annotation Res
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x LIST OF FIGURES 6.1 System module
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xii LIST OF FIGURES
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xiv LIST OF TABLES
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xvi PREFACE My tremendous gratitude
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Chapter 1 Introduction Business pro
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1.2. PROBLEM STATEMENT AND RESEARCH
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1.4. APPROACH AND SCOPE 7 1.4.1 Sem
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1.6. MAJOR CONTRIBUTIONS 9 1.6 Majo
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Chapter 2 Problem Setting In this c
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Figure 2.1: Zachman Enterprise Arch
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2.2. MODELING BASIS 15 meta-model o
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2.3. INFORMATION SYSTEMS AND SEMANT
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2.4. SEMANTIC INTEROPERABILITY 23 3
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2.5. BUSINESS PROCESS MODEL 25 2.5
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2.6. PROCESS KNOWLEDGE MANAGEMENT 2
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2.7. SUMMARY 29 • Creation or imp
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Chapter 3 State of the Art This cha
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3.1. PROCESS MODELING LANGUAGES 33
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3.1. PROCESS MODELING LANGUAGES 35
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Table 3.1: Modeling constructs of d
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3.2. SEMANTIC INTEROPERABILITY AND
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Representation primitives Process P
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9.3. APPLICABILITY VALIDATION IN AN
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9.4. DISCUSSION ON RESULTS OF THE V
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9.4. DISCUSSION ON RESULTS OF THE V
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Part IV Synopsis 163
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166 CHAPTER 10. CONCLUSIONS AND FUT
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Appendix A BPMN This chapter presen
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A.3. CONNECTING OBJECTS 175 Figure
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A.6. BPMN META-MODEL TREE IN METIS
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Appendix B EEML 2005 The language v
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B.2. RECOURSES MODELING DOMAIN 181
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Appendix C SCOR SCOR — Supply Cha
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C.2. LEVEL 2 TOOLKIT 185 Level 1 Me
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C.3. LEVEL 3 PROCESS ELEMENTS 187 F
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Appendix D Algorithm for Semi-Autom
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191 Algorithm 1 Goal Annotation Alg
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Algorithm 4 Goal Annotation Algorit
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195 Algorithm 6 Goal Annotation Alg
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Appendix E GUI of Pro-SEAT The prop
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199 Figure E.3: Mapping meta-model
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201 Figure E.5: Goal annotation UI
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Appendix F Analysis of the Annotati
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F.2. INTEGRATION APPLICATION BASED
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F.2. INTEGRATION APPLICATION BASED
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Appendix G Schema of PSAM and SWRL
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G.1. PSAM IN OWL 211
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G.2. RULE DEFINITIONS IN SWRL 213
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G.2. RULE DEFINITIONS IN SWRL 215
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Appendix H Annotation Results in Ex
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H.2. ANNOTATION OF PM B1 219 xmlns:
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H.3. ANNOTATION OF PM B2 221 Av
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Bibliography [1] ALTOVA. What is th
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BIBLIOGRAPHY 225 [26] Dov Dori. Why
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BIBLIOGRAPHY 227 [52] Ian Horrocks.
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BIBLIOGRAPHY 229 [78] John Krogstie
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BIBLIOGRAPHY 231 [102] Diana Maynar
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BIBLIOGRAPHY 233 [129] OASIS Cover
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BIBLIOGRAPHY 235 [157] Colette Roll
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BIBLIOGRAPHY 237 [185] Systems Thin
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BIBLIOGRAPHY 239 [214] John.A. Zach
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