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

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130 CHAPTER 8. QUALITY EVALUATION OF THE METHOD studies are identified and explained to correspond to the quality categories which are defined in the quality framework. 8.2.1 SEQUAL SEQUAL (SEmiotic QUALity framework) is the latest version of the general quality framework of models and modeling languages which was earlier reported in [73], [76], and [78]. This quality framework was developed with the objective of providing a systematic structure for evaluating the desirable properties for conceptual models. It has been useful in wider context of understanding quality in areas such as requirements engineering [74], enterprise modeling [78] [115], interactive modeling [77], and evaluating and comparing modeling languages such as UML [75], OWL [91]. Compared with other approaches and frameworks available for evaluating modeling approaches, SEQUAL provides a systematic evaluation method and it has three unique properties: • It distinguishes between goals and means, i.e. by separating what to achieve from how to achieve it. • It is closely linked to linguistic and semantic concepts, which particularly including the discussion on the terms of the semiotic theory — syntax, semantics, and pragmatics. • It is based on a constructivistic world-view, recognizing that models are usually created as part of a dialogue between the participants involved in modeling, whose knowledge of the modeling domain and potentially the domain itself changes as modeling takes place. Early version distinguished among three quality categories for conceptual models (syntactic, semantic, and pragmatic) according to steps on the semiotic ladder [33]. The quality goals corresponding to the categories are syntactic correctness, semantic validity and completeness, and comprehension (pragmatic). The framework distinguishes between goals and means to reach the goals. In the later extensions, more quality categories have been added so that the entire semiotic ladder is included, that is, physical, empirical, syntactic, semantic, perceived semantic, pragmatic, social and organizational quality. The main concepts of the framework and their relationships for quality of models are illustrated in Figure 8.1. Physical quality is to check how the externalized model M could be persistent and available enabling the audience to make sense of it. Persistence is usually associated with the protection against loss or damage. It also sometime includes previous versions of the model, if these are relevant. Availability is dependent on its externalization and distributability. Empirical quality focuses on model M itself. Empirical quality deals with the variety of elements distinguished, error frequencies, and ergonomics for CHI (Computer- Human Interaction) for documentation and modeling tools. Syntactic quality is the correspondence between the model M and the language extension L of the modeling language. Syntactical correctness is the goal of this quality
8.2. SETTING FOR THE QUALITY EVALUATION 131 Figure 8.1: SEQUAL framework for discussing quality of models [80] category, which requires that all statements in the model conform to the syntax and vocabulary of the language. Semantic quality is the correspondence between the model M and the modeling domain D. The semantic validity and the semantic completeness are goals for this quality. Perceived semantic quality is the correspondence between the social actors’ interpretation I of a model M and their current knowledge K of the domain D. Pragmatic quality is the correspondence between the model M and the audiences’ interpretation of it I. Usually social pragmatic quality (to what extent people understand the models) and technical pragmatic quality (to what extend tools can be made that can interpret the models) are differentiated. In addition, the pragmatic quality includes to what extent the participants are able to change the domain after interpreting the model or learning from it. The goal for pragmatic quality is comprehension, i.e. the degree to which a model can be understood. Social quality focuses on social actors’ interpretations I. The goal of social quality is agreement among their interpretations. Organizational quality is the correspondence between the model M and the modeling goals G. Organizational goal validity and organizational goal completeness are related to this quality. The quality framework of modeling languages keeps the same concepts used in the quality framework of models. However, the core concept is language extension L but not model externalization M anymore. Six quality categories of language quality are
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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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3.6. SUMMARY 59 In the goal modelin
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Part II Design and Application 61
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64 CHAPTER 4. SEMANTIC ANNOTATION F
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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
Page 169 and 170: 9.2. SWRL FORMULATION 149 RE3.2 RE3
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Page 193 and 194: Appendix A BPMN This chapter presen
Page 195 and 196: A.3. CONNECTING OBJECTS 175 Figure
Page 197 and 198: A.6. BPMN META-MODEL TREE IN METIS
Page 199 and 200: 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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