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

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10 CHAPTER 1. INTRODUCTION Chapter 4 - Semantic Annotation Framework for Process Models introduces our basic semantic annotation framework consisting of profile annotation, meta-model annotation and model annotation. Metadata are defined for profile annotation. A general process ontology is presented as ontological basis for meta-model annotation to cope with various modeling languages applied in different IS solutions. In model annotation, domain ontologies are referenced by model contents to represent systems’ context. A semantic annotation model formalizes the framework with a set of semantic mapping rules. Chapter 5 - Extension Semantic Annotation — Goal Annotation elaborates a goal ontology representation and goal annotation algorithms. Such extension can be used to compare the IS solutions brought by the process models of systems through specifying the intentions of the systems’ owners. Chapter 6 - Pro-SEAT (Process SEmantic Annotation Tool) presents the implementation of the prototype of a semantic annotation tool. System modules provide an overview of the architecture of the prototype. Data structures depict the logical design of the proposed approach. Goal algorithms are implemented to automate the goal annotation. Functionality and graphical user interfaces are illustrated to elucidate the interactions between users and the tool prototype. Chapter 7 - Exemplar Studies and Application System exemplifies the procedure of the approach and the usage of the prototype through two exemplar cases from different business organizations. A process knowledge management system is also outlined by integrating the semantic annotation approach. Chapter 8 - Quality Evaluation of the Method evaluates the quality of the work using a quality framework. The quality evaluation of our annotation approach is discussed according to the quality categories defined in a quality framework. Chapter 9 - Validation of Applicability validates the applicability of the semantic annotation approach in a walkthrough scenario of an integration application of process models. The integration is deployed based on the semantic annotation results of models in the exemplar studies. Chapter 10 - Conclusions and Future Work summarizes the work, and outlines the future work to point out the possible improvements and the interesting directions of further research on semantic interoperability of business process management.
Chapter 2 Problem Setting In this chapter, we establish basic concepts, theoretical and technical background and the context of this research work. Since we work in the information modeling area, we start the study with theories and methodologies in information system engineering discipline. Concepts, standards and relevant issues about semantic interoperability and semantic annotation are then discussed in this chapter. The research target – business process model and its application – business process knowledge management are also discussed concerning the context of the work. 2.1 Models in Information System Engineering A model of a system is defined by OMG 1 as a description or specification of that system and its environment for certain purpose. In the conventional system development lifecycle, models are mainly used in system analysis and design phases and they are not reusable resources after a system is developed. In the modern methods of information system development, models play an important role as reusable IS solutions. MDA 2 is an approach to system development, which increases the power of models in that work. MDA provides a means for using models to direct the course of understanding, design, construction, deployment, operation, maintenance and modification [117]. MDA is initiated with the idea of separating specifications of the operation of a system from details of the way that system uses the capabilities of its platform. The three primary goals of MDA are portability, interoperability and reusability. The objective of MDA is to provide an open, vendor-neutral approach to the challenge of business and technology change [123] by separating different concerns. Three different viewpoint models are distinguished as Computation Independent Model (CIM), Platform Independent Model (PIM) and Platform Specific Model (PSM) [117]. • CIM — A computation independent model is a view of a system from the computation independent viewpoint. A CIM is sometimes called a domain model and a vocabulary that is familiar to the practitioners of the domain in question is used in its specification. 1 Object Management Group, http://www.omg.org/ 2 Model Driven Architecture, http://www.omg.org/mda/ 11
Page 1 and 2: Yun Lin Semantic Annotation for Pro
Page 3: To MY BELOVED HUSBAND HAO DING AND
Page 6 and 7: ii The proposed approach has been i
Page 8 and 9: iv CONTENTS 3 State of the Art 31 3
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Page 14 and 15: x LIST OF FIGURES 6.1 System module
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Page 20 and 21: xvi PREFACE My tremendous gratitude
Page 23 and 24: Chapter 1 Introduction Business pro
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Part II Design and Application 61
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Chapter 8 Quality Evaluation of the
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8.2. SETTING FOR THE QUALITY EVALUA
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8.2. SETTING FOR THE QUALITY EVALUA
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8.3. QUALITY ANALYSIS 135 to those
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8.3. QUALITY ANALYSIS 137 annotatio
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8.3. QUALITY ANALYSIS 139 • G1 -
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8.5. SUMMARY 141 3. Semantic annota
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Chapter 9 Validation of Applicabili
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9.1. VALIDATION DESIGN 145 - RE3.3
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9.2. SWRL FORMULATION 147 Table 9.1
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9.2. SWRL FORMULATION 149 RE3.2 RE3
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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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