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

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102 CHAPTER 6. PRO-SEAT (PROCESS SEMANTIC ANNOTATION TOOL) Figure 6.11: The UI of process knowledge navigator in Pro-SEAT Annotation results are stored in OWL files which are separated from the original models. Links to the original models are specified in the annotation results. It indicates that one model may have more than one annotation file. Different annotation results might be used for different applications. Annotation results are modeled in an annotation schema which is built on GPO – a process meta-model ontology. Hereby, the annotation schema is defined as ontology properties of GPO. The annotation schema can be extended through extending properties of GPO. The annotation schema is independent of this annotation tool and it can be interpreted by any OWL reader. One of the limitations of the tool is a lack of the visual model explorer. Only a tree view of the model hierarchy is provided. Moreover, when re-generating the PSAM models from a meta-model annotation, the results of the model and the goal annotation will be lost. Most of the annotation work is still manual. Automatic annotation using the mapping algorithm can be considered in the further development of the annotation tool.
Chapter 7 Exemplar Studies and Application System Having the methodology guidance and tool support, we can demonstrate the semantic annotation approach in exemplar studies. In the study, we have process models that describe a same business domain (logistics process) but are modeled in different modeling languages and by different enterprises. We need domain and goal ontologies about such a business domain for the annotation. Since there are no formal logistics ontology available, we formalize the SCOR (Supply Chain Operations Reference-model) [163] specifications into logistics domain and goal ontologies using OWL. Following the semantic annotation framework and methods, we deploy the annotation by using Pro- SEAT. Complete annotation results are used in the evaluation phase to validate the applicability of the semantic annotation approach in a process knowledge management application. Therefore, a system architecture is also depicted in this chapter to exploit a process knowledge management application based on the semantic annotation framework. 7.1 Semantic Annotation Procedure The semantic annotation employed in the exemplar studies consists of four phases: profile annotation, meta-model annotation, model annotation and goal annotation (Figure 7.1). In a profile annotation phase, the annotator inputs basic information following the format of metadata which has been defined in Table 4.1. A general process ontology is employed to map process modeling constructs in a meta-model annotation. Based on the meta-model annotation results, PSAM can be initially generated for a new model annotation. The model content represented by PSAM is then annotated with the domain ontology in the model annotation phase. A goal annotation is employed as a succeeding step of the model annotation, i.e. annotating PSAM with goal ontology. Generally, the meta-model, model and goal annotation phases should be implemented step by step in a sequence, but the profile annotation can be made at any time. For example, the URI of the domain ontology can be inputed when the domain ontology is loaded for the model annotation. After completing all the four phases, process models become the process knowledge represented in PSAM models. 103
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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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3.3. GOAL MODELING 49 From the surv
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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 233 [129] OASIS Cover
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BIBLIOGRAPHY 237 [185] Systems Thin
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BIBLIOGRAPHY 239 [214] John.A. Zach
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