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

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68 CHAPTER 4. SEMANTIC ANNOTATION FRAMEWORK the specific and local process meta-model element. The concepts in a local process modeling language usually have the is_a relationship with the concepts from a global process ontology. If the global process ontology can cover all the semantics of the local modeling language (i.e., the local modeling language is a subset of the global process meta model ontology), the annotation work can keep the complete semantics of the local modeling language. If the local process modeling language is more expressive than the global process ontology (i.e., the set of notations of the local modeling language is larger than the global one), the model will lose some of the semantics which are not annotated by the global process ontology. For those lost semantics, referencing the meta-model of the modeling language is necessary. A domain ontology provides the standardized terminology and conceptualization of a particular domain. We suppose that a certain domain ontology is agreed and used to reconcile the semantics of model contents. The ontological concepts are referenced by model contents through simple URIs or semantic relationships. Figure 4.4 provides a depiction of the basic idea of ontology-based semantic annotation. Process models PM and PN are respectively represented in process modeling languages M and N. The notations used in process models are instances of modeling concepts defined in meta-models. For example, the notation for PM1, PM2 and PM4 is an instance of M A , and PN1, PN2 and PN3 are instances of N A . The semantics of the notations are defined in meta-models. In order to reconcile the semantics of the notations, a process ontology is used to mediate the mapping between meta-models M and N. For instance, M A and N A are annotated with a same ontological concept PO x in the process ontology, which means notations of M A in PM (PM1, PM2 and PM4) stand for the same meta-model element as notations of N A in PN (PN1, PN2 and PN3). However, model contents in those notations should also be semantically reconciled to understand both models, i.e. what domain phenomenon the notations represent. A domain ontology is referenced to annotate model content. Usually the model contents represented by the same meta-model element are comparable. For example, the contents of PM1, PM2 and PM4 should be reconciled with PN1, PN2 and PN3. Since PM1 and PN1 are annotated with a same domain ontological concept DO x , they are interpreted as semantically equal concepts when comparing the two models. If the contents of two model constructs with different meta-model elements reference to a same domain ontological concept, they are not considered as semantically equal. Although the contents of PM3 and PN4 have a same ontology reference DO y , they are not same because they do not share a same modeling ontological concept at the meta level (PO y for PM3 and PO z for PN4). In this way, various representations of process models are aligned and reconciled through the reference ontologies, i.e. the process ontology and domain ontology. 4.2.2 Annotation aspects Annotation in this work is intended to expose the process knowledge carried by heterogeneous process models. In general, the annotation should be able to provide both an overview and a sophisticated comprehension of the process knowledge. We therefore include a profile annotation to profile process models as products. In the profile annotation, a set of metadata is defined to describe the significant characteristics of a
4.3. PROFILE ANNOTATION 69 process model from a general view. Comprehending a process model depends on the understanding of the semantic representations of process modeling languages and model contents. We use meta-model and model annotation to catch and represent the process knowledge in the models through building reference relationships between models and ontologies. Technically, process models to be annotated are serialized into XML representations. During the annotation, the meta-model schema of process models are mapped to a common process ontology in OWL. Model contents in the XML file are transformed into the OWL annotation model. Domain ontologies are referenced by the model contents in the OWL annotation model. 4.3 Profile Annotation Basic and characteristic features of a process model are described by a set of metadata in a profile annotation. A profile contains information about a process model such as the problem domain of the model, the name of the model and the location of the model etc. We categorize metadata elements for the profile annotation according to four types of metadata — administrative, descriptive, preservation, technical and use [4] (see Table 4.1). • Administrative: Metadata used in managing and administering information resources. • Descriptive: Metadata used to describe or identify information resources. • Preservation: Metadata related to the preservation management of information resources. • Technical: Metadata related to how a system functions or Metadata behave. • Use: Metadata related to the level and type of use of information resources. Usually, the profile information is manually input by annotators. In order to prevent the semantic heterogeneity in the input values, a set of categories and taxonomy are chosen to be referenced for profile annotation. For example, a list of standard abbreviations for the natural languages (e.g. "EN" for English) are predefined for the value of dc:language. 4.4 Meta-model Annotation Semantic heterogeneity problems of diverse process modeling languages can be solved through mapping two modeling languages to each other, or mapping languages to one common process modeling language. Meta-model annotation in our framework deals with this problem by mapping different meta-mode elements to ontological concepts in a process ontology. A process ontology is not supposed to be a new process modeling language but provide a way to represent process knowledge. Therefore, compared with certain process modeling languages, the process ontology provides only general semantics for process modeling but essential semantics for process knowledge.
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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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Page 49 and 50: 2.7. SUMMARY 29 • Creation or imp
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Page 53 and 54: 3.1. PROCESS MODELING LANGUAGES 33
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Page 69 and 70: 3.3. GOAL MODELING 49 From the surv
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Page 81: Part II Design and Application 61
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118 CHAPTER 7. EXEMPLAR STUDIES AND
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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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