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

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110 CHAPTER 7. EXEMPLAR STUDIES AND APPLICATION SYSTEM Figure 7.9: The delivery process to shops of enterprise B in EEML The delivery processing of PM B2 describes only a part of the sales logistics process. PM B2 in EEML is illustrated in Figure 7.7, and some of the process detail is displayed in Figure 7.8 and Figure 7.9. 7.3 SCOR Reference Ontology SCOR is a process reference model that has been developed and endorsed by the Supply- Chain Council as the cross-industry standard diagnostic tool for supply-chain management. A SCOR reference model has been developed to describe the standard business activities associated with all phases of satisfying a customer’s demand. As standards, the model can be formalized as a reference ontology for supply-chain management domain. There are three level process details in the reference model. The top level defines the scope and content of SCOR. Five process types — Plan, Source, Make, Deliver and Return are defined at this level. The second level is the configuration level defining the core "process categories". The third level is the process element level, decomposing the process categories into the process elements. The process element level consists of process element definitions, process element information inputs, and outputs, process performance metrics, best practices, system capabilities required to support best practices, and systems/tools. As an example, a logic flow of the SCOR level 3 process elements is depicted in Figure 7.10. The level 3 process elements provide enough details of references for domain activities. In this work, we model domain ontology concepts based on the SCOR process elements at level 3 for model annotation purpose. The SCOR ontology from the IN- TEROP project [62] is extended. The extended ontologies include SCOR_INPUT_OUTPUT, SCOR_MGM_PROCESS and SCOR_ORGANISATION. SCOR_INPUT_OUTPUT are objects which are needed or produced by SCOR process elements. SCOR_MGM_PROCESS are the SCOR process elements at level 3 which are organized in a hierarchy following the SCOR
7.3. SCOR REFERENCE ONTOLOGY 111 Figure 7.10: SCOR S1 process of sourcing stocked product [164] levels (from level 1 to level 3). SCOR_ORGANISATION are organizations/persons who are involved in the process elements. The goal ontology in this domain is also from SCOR. Usually the hard goals are derived from process elements and also from their inputs and outputs. Performance attributes defined in SCOR can be modeled as a set of General Soft Goal Category such as Reliability, Responsiveness, Flexibility, Cost, and Assets. Domain specific soft goals are derived from the metrics of performance attributes [167]. The SCOR ontology is formalized in OWL. To organize those concepts, we categorize domain concepts with the 3A concepts (Activity, Artifact, Actor-role) defined in GPO. The purpose of the categories is to establish the mapping relationship between a PSAM model and the reference ontology when annotation. The categories and concepts are modelled as OWL Classes, and they are organized by a subsumption hierarchy. The ontology concepts which are organized in "SCOR_MGMT_PROCESS" are sub-classes of Activity, the input/output ontology concepts ("SCOR_INPUT_OUTPUT") are sub-classes of Artifact and the organizational ontology concepts ("SCOR_ORGANIZATIONAL") are sub-classes of Actor-role.
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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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3.4. SEMANTIC ANNOTATION METHODS AN
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Page 79 and 80: 3.6. SUMMARY 59 In the goal modelin
Page 81: Part II Design and Application 61
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Page 161 and 162: 8.5. SUMMARY 141 3. Semantic annota
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Page 165 and 166: 9.1. VALIDATION DESIGN 145 - RE3.3
Page 167 and 168: 9.2. SWRL FORMULATION 147 Table 9.1
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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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