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

More documents

Recommendations

Info

144 CHAPTER 9. VALIDATION OF APPLICABILITY modeling experts and domain specialists, who provide reliable mappings. Accuracy of the annotation is hereby not taken into account in the evaluation. 9.1.1 Application requirements In this applicational scenario, users need to navigate models for browsing the process knowledge of the legacy IS solutions, search interesting knowledge candidates for building a new solution, select suitable model fragments from the candidates, and reuse the selected model fragments in a knowledge-based integration. We therefore elicit the following requirements to implement the application. The requirements are associated with the annotation goals (G1-G4) identified in section 8.2.2. If the annotation method fulfills the requirements of the application, it satisfies the annotation goals too. • RE1 - Navigation requirements. For the purpose of browsing knowledge, navigate process models (PM A , PM B1 and PM B2 ) (related to G1). Such a requirement can be decomposed into following sub-requirements by specifying the interests of process properties. – RE1.1 - List Activities and their sub-Activities. – RE1.2 - List Activities and their preceding or succeeding Activities. – RE1.3 - List Activities and their Artifacts. – RE1.4 - List Activities and their Actor-roles. – RE1.5 - List Activities and their Preconditions or Postconditions. • RE2 - Search requirements. For the purpose of locating interesting knowledge candidates, search the corresponding process model fragments across different business models by using the SCOR domain ontology (related to G2). Such a requirement can be decomposed into following sub-requirements by specifying the interests of ontological concepts. – RE2.1 - Find the model fragments of process models that reference to SCOR Management Process. – RE2.2 - Find the model fragments of process models that reference to SCOR Input/Output. – RE2.3 - Find the model fragments of process models that reference to SCOR Organizational. – RE2.4 - Find the model fragments of process models that reference to SCOR Goal. • RE3 - Semantics checking requirements. For the purpose of selecting suitable model fragments, check the semantics of the process models and the annotation results (related to G3). Such a requirement can be decomposed into following subrequirements by specifying the interests of process semantics defined in PSAM. – RE3.1 - Check the Artifacts related to the Input/Output of Activities. – RE3.2 - Check the Activity sequences.
9.1. VALIDATION DESIGN 145 – RE3.3 - Check the Artifacts in sub-Activities. – RE3.4 - Check the Actor-roles in sub-Activities. – RE3.5 - Check the goal annotations in sub-Activities. – RE3.6 - Check the Precondition/Postcondition of Activities. – RE3.7 - Check the information flow from Outputs to Inputs. • RE4 - Knowledge discovery requirements. For the purpose of reusing and integrating model fragments, acquire the implicit knowledge across different models through reasoning on ontological relationships (related to G4). Such a requirement can be decomposed into following sub-requirements by specifying the interests of potential relationships between process properties of different models. – RE4.1 - Find out semantic relationships between the Activities of different process models. – RE4.2 - Find out semantic relationships between the Artifacts of different process models. – RE4.3 - Find out semantic relationships between the Actor-roles of different process models. – RE4.4 - Find out goal relations between the Activities of different process models. – RE4.5 - Find out possible integration points among different process models. 9.1.2 SWRL rules and tool SWRL is an acronym for Semantic Web Rule Language. As stated in [149]: It is intended to be the rule language of the Semantic Web. SWRL is based on a combination of the OWL DL and OWL Lite sub-languages of the OWL Web Ontology Language. It allows users to write Horn-like rules to reason about OWL individuals and to infer new knowledge about those individuals. These rules are expressed in terms of OWL concepts. SWRL is more expressive that OWL DL alone yet retains its formal semantics. It does so, however, at the expense of decidability. We use SWRL to formalize the application requirements for each annotation model – a PSAM instance model in OWL. Running the SWRL rules shows the computational capability of the annotation models, which is one of the benefits of the proposed approach. Analyzing the rule-execution results helps check what knowledge can be derived from the annotation results and how the results fulfill the application requirements. SWRL SWRL rules are of the form of an implication between an antecedent (body) and consequent (head). The intended meaning can be read as: whenever the conditions specified in the antecedent hold, then the conditions specified in the consequent must also hold. SWRL rules are written in terms of OWL classes, properties and individuals.
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
Page 10 and 11:
vi CONTENTS 7.5.2 Semantic reasonin
Page 12 and 13:
viii CONTENTS H PSAM Annotation Res
Page 14 and 15:
x LIST OF FIGURES 6.1 System module
Page 16 and 17:
xii LIST OF FIGURES
Page 18 and 19:
xiv LIST OF TABLES
Page 20 and 21:
xvi PREFACE My tremendous gratitude
Page 23 and 24:
Chapter 1 Introduction Business pro
Page 25 and 26:
1.2. PROBLEM STATEMENT AND RESEARCH
Page 27 and 28:
1.4. APPROACH AND SCOPE 7 1.4.1 Sem
Page 29 and 30:
1.6. MAJOR CONTRIBUTIONS 9 1.6 Majo
Page 31 and 32:
Chapter 2 Problem Setting In this c
Page 33 and 34:
Figure 2.1: Zachman Enterprise Arch
Page 35 and 36:
2.2. MODELING BASIS 15 meta-model o
Page 37 and 38:
2.3. INFORMATION SYSTEMS AND SEMANT
Page 39 and 40:
Page 41 and 42:
Page 43 and 44:
2.4. SEMANTIC INTEROPERABILITY 23 3
Page 45 and 46:
2.5. BUSINESS PROCESS MODEL 25 2.5
Page 47 and 48:
2.6. PROCESS KNOWLEDGE MANAGEMENT 2
Page 49 and 50:
2.7. SUMMARY 29 • Creation or imp
Page 51 and 52:
Chapter 3 State of the Art This cha
Page 53 and 54:
3.1. PROCESS MODELING LANGUAGES 33
Page 55 and 56:
3.1. PROCESS MODELING LANGUAGES 35
Page 57 and 58:
Table 3.1: Modeling constructs of d
Page 59 and 60:
3.2. SEMANTIC INTEROPERABILITY AND
Page 61 and 62:
Page 63 and 64:
Page 65 and 66:
Page 67 and 68:
Representation primitives Process P
Page 69 and 70:
3.3. GOAL MODELING 49 From the surv
Page 71 and 72:
3.4. SEMANTIC ANNOTATION METHODS AN
Page 73 and 74:
Page 75 and 76:
Page 77 and 78:
Page 79 and 80:
3.6. SUMMARY 59 In the goal modelin
Page 81:
Part II Design and Application 61
Page 84 and 85:
64 CHAPTER 4. SEMANTIC ANNOTATION F
Page 86 and 87:
Page 88 and 89:
Page 90 and 91:
Page 92 and 93:
Page 94 and 95:
Page 96 and 97:
Page 98 and 99:
Page 100 and 101:
Page 102 and 103:
Page 104 and 105:
84 CHAPTER 5. GOAL ANNOTATION proce
Page 106 and 107:
86 CHAPTER 5. GOAL ANNOTATION in a
Page 108 and 109:
88 CHAPTER 5. GOAL ANNOTATION • i
Page 110 and 111:
90 CHAPTER 5. GOAL ANNOTATION 5.5 G
Page 112 and 113:
92 CHAPTER 5. GOAL ANNOTATION
Page 114 and 115: 94 CHAPTER 6. PRO-SEAT (PROCESS SEM
Page 120 and 121: 100 CHAPTER 6. PRO-SEAT (PROCESS SE
Page 122 and 123: 102 CHAPTER 6. PRO-SEAT (PROCESS SE
Page 124 and 125: 104 CHAPTER 7. EXEMPLAR STUDIES AND
Page 149 and 150: Chapter 8 Quality Evaluation of the
Page 151 and 152: 8.2. SETTING FOR THE QUALITY EVALUA
Page 153 and 154: 8.2. SETTING FOR THE QUALITY EVALUA
Page 155 and 156: 8.3. QUALITY ANALYSIS 135 to those
Page 157 and 158: 8.3. QUALITY ANALYSIS 137 annotatio
Page 159 and 160: 8.3. QUALITY ANALYSIS 139 • G1 -
Page 161 and 162: 8.5. SUMMARY 141 3. Semantic annota
Page 163: Chapter 9 Validation of Applicabili
Page 167 and 168: 9.2. SWRL FORMULATION 147 Table 9.1
Page 169 and 170: 9.2. SWRL FORMULATION 149 RE3.2 RE3
Page 171 and 172: 9.3. APPLICABILITY VALIDATION IN AN
Page 179 and 180: 9.4. DISCUSSION ON RESULTS OF THE V
Page 181 and 182: 9.4. DISCUSSION ON RESULTS OF THE V
Page 183: Part IV Synopsis 163
Page 186 and 187: 166 CHAPTER 10. CONCLUSIONS AND FUT
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
Page 201 and 202: B.2. RECOURSES MODELING DOMAIN 181
Page 203 and 204: Appendix C SCOR SCOR — Supply Cha
Page 205 and 206: C.2. LEVEL 2 TOOLKIT 185 Level 1 Me
Page 207 and 208: C.3. LEVEL 3 PROCESS ELEMENTS 187 F
Page 209 and 210: Appendix D Algorithm for Semi-Autom
Page 211 and 212: 191 Algorithm 1 Goal Annotation Alg
Page 213 and 214: Algorithm 4 Goal Annotation Algorit
Page 215 and 216:
195 Algorithm 6 Goal Annotation Alg
Page 217 and 218:
Appendix E GUI of Pro-SEAT The prop
Page 219 and 220:
199 Figure E.3: Mapping meta-model
Page 221 and 222:
201 Figure E.5: Goal annotation UI
Page 223 and 224:
Appendix F Analysis of the Annotati
Page 225 and 226:
F.2. INTEGRATION APPLICATION BASED
Page 227 and 228:
F.2. INTEGRATION APPLICATION BASED
Page 229 and 230:
Appendix G Schema of PSAM and SWRL
Page 231 and 232:
G.1. PSAM IN OWL 211
Page 233 and 234:
G.2. RULE DEFINITIONS IN SWRL 213
Page 235 and 236:
G.2. RULE DEFINITIONS IN SWRL 215
Page 237 and 238:
Appendix H Annotation Results in Ex
Page 239 and 240:
H.2. ANNOTATION OF PM B1 219 xmlns:
Page 241 and 242:
H.3. ANNOTATION OF PM B2 221 Av
Page 243 and 244:
Bibliography [1] ALTOVA. What is th
Page 245 and 246:
BIBLIOGRAPHY 225 [26] Dov Dori. Why
Page 247 and 248:
BIBLIOGRAPHY 227 [52] Ian Horrocks.
Page 249 and 250:
BIBLIOGRAPHY 229 [78] John Krogstie
Page 251 and 252:
BIBLIOGRAPHY 231 [102] Diana Maynar
Page 253 and 254:
BIBLIOGRAPHY 233 [129] OASIS Cover
Page 255 and 256:
BIBLIOGRAPHY 235 [157] Colette Roll
Page 257 and 258:
BIBLIOGRAPHY 237 [185] Systems Thin
Page 259:
BIBLIOGRAPHY 239 [214] John.A. Zach
show all

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

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?