Semantic Annotation for Process Models: - Department of Computer ...
Semantic Annotation for Process Models: - Department of Computer ... Semantic Annotation for Process Models: - Department of Computer ...
112 CHAPTER 7. EXEMPLAR STUDIES AND APPLICATION SYSTEM Table 7.1: OWL definition of the SCOR ontology OWL Ontology Class Subsumption OWL Properties Property Range Relation owl:subClassOf hasInput multiple SCOR_MGMT_PROCESS Activity SCOR_INPUT_OUTPUT hasOutput multiple SCOR_INPUT_OUTPUT precedes multiple SCOR_MGMT_PROCESS isPrecededBy multiple SCOR_MGMT_PROCESS owl:subClassOf isInputTo multiple SCOR_INPUT_OUTPUT Artifact SCOR_MGMT_PROCESS isOutputOf multiple SCOR_MGMT_PROCESS has_state (data property inherited from Artifact SCOR_ORGANIZATIONAL owl:subClassOf Actor-role has sub-Class has_parts multiple Goal Hard Goal, Goal Soft Goal part_of multiple Goal targetActivity multiple Activity targetArtifact multiple Artifact targetRole multiple Actor-role targetConstraint (data property) Each SCOR_MGMT_PROCESS has object properties hasInput and hasOutput to specify inputs and outputs of each process element. The object properties precedes and isPrecededBy indicate logic flows between the process elements. Inversely, SCOR_INPUT_OUTPUT has the object properties isInputTo and isOutputOf to relate itself to SCOR_MGMT_PROCESS. A data property has_state is defined as a property of Artifact. This property can be used associated with isInputTo and isOutputOf properties to indicate that a same artifact with different states represents different inputs/outputs. Goal ontology concepts are organized into Hard and Soft Goals. Soft goals are further organized into some general soft goal categories. We integrate the domain ontology and goal ontology into one OWL file, because they are both derived from SCOR descriptions. According to the semantic representation of the goal ontology in Chapter 5, the values of the object properties targetActivity, targetArtifact, and targetRole are from the domain ontology Activity, Artifact and Actor-role respectively. TargetConstraint is modeled as a data property since there is no corresponding ontological definition in the domain ontology. A pair of inverse properties has_parts and part_of are defined for a goal concept to represent the semantics of goal decomposition. An OWL model of the SCOR ontology is presented in Table 7.1. The identified domain and goal concepts from the SCOR specifications are modeled as sub-Classes of the above categories. Values of the properties for a SCOR Class are specified through the OWL restrictions. As examples, Figure 7.11, Figure 7.12, Figure 7.13 and Figure 7.14 illustrate the sub-Classes of the SCOR_MGMT_PROCESS, SCOR_INPUT_OUTPUT, Hard Goal and Soft Goal in the Protégé-OWL editor.
7.4. ANNOTATION OF PROCESS MODELS WITH PRO-SEAT 113 Figure 7.11: SCOR process element S1.2 Receive Product in Protégé-OWL editor Figure 7.12: SCOR input/output Sourced Product On Order in Protégé-OWL editor 7.4 Annotation of Process Models with Pro-SEAT In this section, we will describe the annotation of PM A , PM B1 and PM B2 with the Pro- SEAT annotation tool. The annotation follows our semantic annotation framework and approach, including profile annotation, meta-model annotation, model annotation and goal annotation. 7.4.1 Profile annotation The descriptive and technical information about models in the profiles are important in this scenario. Title and description of models may help to identify the model content in general. The title of PM A is "sales logistics process" and the main processing is depicted in the description. The titles of PM B1 and PM B2 are "stock logistics process" and "delivery logistics process" respectively. In this scenario, the three models are classified under the same category "Business and Economy" [211] and domain is "SCO
- Page 81: Part II Design and Application 61
- Page 84 and 85: 64 CHAPTER 4. SEMANTIC ANNOTATION F
- Page 86 and 87: 66 CHAPTER 4. SEMANTIC ANNOTATION F
- Page 88 and 89: 68 CHAPTER 4. SEMANTIC ANNOTATION F
- Page 90 and 91: 70 CHAPTER 4. SEMANTIC ANNOTATION F
- Page 92 and 93: 72 CHAPTER 4. SEMANTIC ANNOTATION F
- Page 94 and 95: 74 CHAPTER 4. SEMANTIC ANNOTATION F
- Page 96 and 97: 76 CHAPTER 4. SEMANTIC ANNOTATION F
- Page 98 and 99: 78 CHAPTER 4. SEMANTIC ANNOTATION F
- Page 100 and 101: 80 CHAPTER 4. SEMANTIC ANNOTATION F
- Page 102 and 103: 82 CHAPTER 4. SEMANTIC ANNOTATION F
- 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 116 and 117: 96 CHAPTER 6. PRO-SEAT (PROCESS SEM
- Page 118 and 119: 98 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 126 and 127: 106 CHAPTER 7. EXEMPLAR STUDIES AND
- Page 128 and 129: 108 CHAPTER 7. EXEMPLAR STUDIES AND
- Page 130 and 131: 110 CHAPTER 7. EXEMPLAR STUDIES AND
- Page 134 and 135: 114 CHAPTER 7. EXEMPLAR STUDIES AND
- Page 136 and 137: 116 CHAPTER 7. EXEMPLAR STUDIES AND
- Page 138 and 139: 118 CHAPTER 7. EXEMPLAR STUDIES AND
- Page 140 and 141: 120 CHAPTER 7. EXEMPLAR STUDIES AND
- Page 142 and 143: 122 CHAPTER 7. EXEMPLAR STUDIES AND
- Page 144 and 145: 124 CHAPTER 7. EXEMPLAR STUDIES AND
- Page 146 and 147: 126 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 and 164: Chapter 9 Validation of Applicabili
- 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
- Page 171 and 172: 9.3. APPLICABILITY VALIDATION IN AN
- Page 173 and 174: 9.3. APPLICABILITY VALIDATION IN AN
- Page 175 and 176: 9.3. APPLICABILITY VALIDATION IN AN
- Page 177 and 178: 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
7.4. ANNOTATION OF PROCESS MODELS WITH PRO-SEAT 113<br />
Figure 7.11: SCOR process element S1.2 Receive Product in Protégé-OWL editor<br />
Figure 7.12: SCOR input/output Sourced Product On Order in Protégé-OWL editor<br />
7.4 <strong>Annotation</strong> <strong>of</strong> <strong>Process</strong> <strong>Models</strong> with Pro-SEAT<br />
In this section, we will describe the annotation <strong>of</strong> PM A , PM B1 and PM B2 with the Pro-<br />
SEAT annotation tool. The annotation follows our semantic annotation framework and<br />
approach, including pr<strong>of</strong>ile annotation, meta-model annotation, model annotation and<br />
goal annotation.<br />
7.4.1 Pr<strong>of</strong>ile annotation<br />
The descriptive and technical in<strong>for</strong>mation about models in the pr<strong>of</strong>iles are important in<br />
this scenario. Title and description <strong>of</strong> models may help to identify the model content<br />
in general. The title <strong>of</strong> PM A is "sales logistics process" and the main processing is<br />
depicted in the description. The titles <strong>of</strong> PM B1 and PM B2 are "stock logistics process"<br />
and "delivery logistics process" respectively. In this scenario, the three models are<br />
classified under the same category "Business and Economy" [211] and domain is "SCO
Change language