Semantic Annotation for Process Models: - Department of Computer ...
Semantic Annotation for Process Models: - Department of Computer ... Semantic Annotation for Process Models: - Department of Computer ...
116 CHAPTER 7. EXEMPLAR STUDIES AND APPLICATION SYSTEM After the meta-model annotation, three models can be represented using GPO concepts through the meta-model mapping. The contents in different models are then expressed in a same process knowledge representation language, e.g. an Activity named "check availability of delivery item" has an Actor − role called "logistics department" in enterprise A (originally represented in PM A as a logical process "check availability of delivery item" in a swimlane "logistics department" in BPMN) vs. an Activity named "check stock" has an Actor − role called "logistics department" in enterprise B (originally represented in PM B2 as an organization object "logistics department" participates in the task "check stock" in EEML). 7.4.3 Model annotation In the model annotation phase, model elements as GPO instances will be annotated with reference ontologies. Since PM A and PM B2 are about the delivery process, the reference ontologies for annotating the Activities are mainly from the category DELIVER under SCOR_MGMT_PROCESS. Furthermore, the products are stocked products so that the process elements of D1 Deliver Stocked Product are the corresponding references. For PM B1 , most of the Activities refer to the process elements of S1 Source Stocked Product. Artifacts and Actor-roles refer to the SCOR_INPUT_OUTPUT and SCOR_ORGANIZATIONAL for all three models. Relationships between model elements such as has_subActivity, has_Input, has_Output, etc. (defined in GPO) should be instantialized in the model annotation phase. Some of the relationships can be directly transformed from the original process models, and some are specified by the annotation user. Such annotations can enrich the implicit semantics in the original models or compensate for the lost information caused by the transformation from the meta-model annotation. 7.4.4 Goal annotation For the goal annotation, the semi-automatic goal annotation function of Pro-SEAT is run in the exemplar studies. Through the execution of goal annotation algorithms defined in section 6.3, the possible goal annotation results can be deduced automatically based on the model annotation information. Pro-SEAT provides a list of goal options by matching the SCOR goal ontology with the PSAM models. From the list, annotation users then select suitable goals manually to annotate the model fragments. 7.4.5 Annotation results Complete annotation results of three models are presented in Appendix H in OWL. For the sake of representation clarity and limited space, in this section we represent parts of the annotation results of three models in Table 7.3, Table 7.4 and Table 7.5. The first column of the tables lists the PSAM Activity instances which are also the model elements of Logic Process in PM A or Task in PM B1 and P B2 . The second column is the model annotation result: the Activities are annotated with SCOR process elements or categories through the semantic relationships same_as, kind_of and phase_of. The third and fourth columns are the goal annotation results. The SCOR goal ontology is associated with each Activity instance in the case of achieving certain hard goals,
7.5. PROCESS KNOWLEDGE MANAGEMENT SYSTEM 117 positively and/or negatively satisfying soft goals. Details of the annotation analysis are depicted in Appendix F. After annotating all the Activities, Artifact, Actor-role, Input and Output of a PSAM model with domain ontology, the knowledge representation of those process models is aligned with the SCOR ontology. Thus the process knowledge is explicit and open to a third party who is interested in model exchange, system integration and business cooperation in the SCOR domain. Goal-oriented analysis and goal-driven search of process models and model fragments can be deployed based on the SCOR goal ontology which is referenced in the annotation. For instance, the annotation information can help an analyst to find out the processes which are related to the verification costs. 7.5 Process Knowledge Management System Based on Semantic Annotation Generally knowledge management (KM) refers to a range of practices used by organizations to create, codify, and disseminate knowledge for reuse, awareness and learning within or across the organization. In the context of the thesis, process models from different enterprise systems are distributed process knowledge to be managed for the cooperation business. The hypothesis is that process models have been represented in our process annotation models — PSAM models in OWL, which is a way to represent process knowledge. However, enterprises need a service to manage the desired knowledge. Therefore, the management service should provide the query functions to set users’ search conditions and then return search results. The search conditions can be set based on profiles or contents of process models. The query should not only be keyword-based but also ontology-based, so the semantic relationships among queries and models/model fragments should be machine-interpretable during the query. Moreover, users need the system to help them "discover" knowledge, to do this users need only provide the business goals and the system should return the process models/knowledge fulfilling the goals. Since the process knowledge is represented by process models, the search results are models or model fragments. No matter which way to represent the models — the visual display or the textual description, the knowledge management service should allow the users to navigate the knowledge conveniently, such as providing both a complete view and a partial view of models/model fragments. Following our semantic annotation framework, an enterprise can use the semantic annotation client tool to annotate model resources. The client tool sends the annotation models to the server through which the process knowledge is stored into a knowledge repository. Since the annotation models are represented in OWL — XML-based files, the repository is an XML-based repository. The process knowledge query, discovery and navigation functions can also be implemented as user interfaces on client side. Knowledge users can edit the search queries and business goals on the client side and submit the queries and goals to the server. The search and discovery services are executed on the server. The search results are returned from the server to clients. Finally, users can navigate the returned process knowledge/models on the client side.
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116 CHAPTER 7. EXEMPLAR STUDIES AND APPLICATION SYSTEM<br />
After the meta-model annotation, three models can be represented using GPO<br />
concepts through the meta-model mapping. The contents in different models are then<br />
expressed in a same process knowledge representation language, e.g. an Activity named<br />
"check availability <strong>of</strong> delivery item" has an Actor − role called "logistics department" in<br />
enterprise A (originally represented in PM A as a logical process "check availability <strong>of</strong><br />
delivery item" in a swimlane "logistics department" in BPMN) vs. an Activity named<br />
"check stock" has an Actor − role called "logistics department" in enterprise B (originally<br />
represented in PM B2 as an organization object "logistics department" participates in the<br />
task "check stock" in EEML).<br />
7.4.3 Model annotation<br />
In the model annotation phase, model elements as GPO instances will be annotated<br />
with reference ontologies. Since PM A and PM B2 are about the delivery process, the reference<br />
ontologies <strong>for</strong> annotating the Activities are mainly from the category DELIVER<br />
under SCOR_MGMT_PROCESS. Furthermore, the products are stocked products so that<br />
the process elements <strong>of</strong> D1 Deliver Stocked Product are the corresponding references.<br />
For PM B1 , most <strong>of</strong> the Activities refer to the process elements <strong>of</strong> S1 Source<br />
Stocked Product. Artifacts and Actor-roles refer to the SCOR_INPUT_OUTPUT and<br />
SCOR_ORGANIZATIONAL <strong>for</strong> all three models.<br />
Relationships between model elements such as has_subActivity, has_Input,<br />
has_Output, etc. (defined in GPO) should be instantialized in the model annotation<br />
phase. Some <strong>of</strong> the relationships can be directly trans<strong>for</strong>med from the original process<br />
models, and some are specified by the annotation user. Such annotations can enrich<br />
the implicit semantics in the original models or compensate <strong>for</strong> the lost in<strong>for</strong>mation<br />
caused by the trans<strong>for</strong>mation from the meta-model annotation.<br />
7.4.4 Goal annotation<br />
For the goal annotation, the semi-automatic goal annotation function <strong>of</strong> Pro-SEAT<br />
is run in the exemplar studies. Through the execution <strong>of</strong> goal annotation algorithms<br />
defined in section 6.3, the possible goal annotation results can be deduced automatically<br />
based on the model annotation in<strong>for</strong>mation. Pro-SEAT provides a list <strong>of</strong> goal options<br />
by matching the SCOR goal ontology with the PSAM models. From the list, annotation<br />
users then select suitable goals manually to annotate the model fragments.<br />
7.4.5 <strong>Annotation</strong> results<br />
Complete annotation results <strong>of</strong> three models are presented in Appendix H in OWL. For<br />
the sake <strong>of</strong> representation clarity and limited space, in this section we represent parts<br />
<strong>of</strong> the annotation results <strong>of</strong> three models in Table 7.3, Table 7.4 and Table 7.5. The<br />
first column <strong>of</strong> the tables lists the PSAM Activity instances which are also the model<br />
elements <strong>of</strong> Logic <strong>Process</strong> in PM A or Task in PM B1 and P B2 . The second column is the<br />
model annotation result: the Activities are annotated with SCOR process elements or<br />
categories through the semantic relationships same_as, kind_<strong>of</strong> and phase_<strong>of</strong>. The<br />
third and fourth columns are the goal annotation results. The SCOR goal ontology<br />
is associated with each Activity instance in the case <strong>of</strong> achieving certain hard goals,
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