 | Level: Intermediate Naveen Balani (banaveen@in.ibm.com), Development Manager, IBM
Rohit Sardesai (rohitsardesai@in.ibm.com), Software Engineer, IBM
Ravikumar Vishwakarma (viraviku@in.ibm.com), Software Engineer, IBM
Manojkumar Pal (palmanojkumar@in.ibm.com), Software Engineer, IBM
Matt Sanchez (msanchez@us.ibm.com), Senior Technical Staff Member, IBM
25 Jun 2008 Learn how you can leverage the features of WebSphere®
Business Services Fabric to build composite business applications that support
dynamic binding and orchestration. In Part 2, you'll learn how to model the
variability points in the business process as ontology extensions using the
Fabric Modeling Tool.
Introduction
Part 2 of this series describes the requirements of the application that
we're going to build and deploy in WebSphere Process Server V6.1 to
interact with WebSphere Business Services Fabric (hereafter called
Fabric). The application simulates an auto loan procurement system that
accepts user information and responds with approval or rejection of the
loan request. You'll learn how to build ontology extensions to capture the
points of variability in a business process and enable dynamic binding, in
which the service endpoint is discovered dynamically at service
invocation.
Fabric eliminates the need for hard-coded static binding of services and
provides late binding of services to enable more generalized process
models. With Fabric, you can define an abstract business process and
capture the process variability points in business policies that govern
the run-time behavior and insulate process from changes. Fabric makes it
possible to dynamically change the behavior of business processes in order
to respond effectively to changing business needs.
Prerequisites
In order to complete the steps in this article, you'll need the following:
- Rational® Software Architect V7 with the following features
installed:
- Extensibility features (all features except the Reusable Asset
Specification)
- WSDL and XSD modeling and transformations
- IBM® Business Services Fabric Modeling Tool
- Fabric Business Glossary and Fabric Ontology Profiles (available in
the modeling folder of the Fabric V6.1 Tool Pack)
- Fabric Core Stubs (available in the modeling folder of the Fabric V6.1
Tool Pack)
About the use
case
In future parts in this series, you'll develop a composite business
application that simulates an auto loan procurement process. When a user
submits a request for loan, it will be processed by the system, which will
perform the following tasks:
- Credit verification
- License verification
- Loan provisioning
Table 1 describes the key elements of the use case:
Table 1. Auto loan procurement system
use case elements
| Use case element | Description |
|---|
| Auto loan procurement system | Processes loan request for user |
|---|
| Use case description | The user submits a loan request to purchase an automobile. |
|---|
| Primary actor | Any user |
|---|
| Basic flow | Credit verification and license verification is successful, loan
is approved with varying interest rates. |
|---|
| Alternate flows | Credit verification or license verification fails. The loan
request is rejected. |
|---|
Implementing the
auto loan process
Figure 1 illustrates the flow for the auto loan procurement system.
Figure 1. Flow chart for
the auto loan procurement system
As illustrated in Figure 1, the auto loan process needs to integrate with
various third-party service providers, like LicenseVerificationService and
LoanProviderService. The third-party service providers expose their
functions as Web services.
As you implement the auto loan procurement process, you would typically use
various if...else conditions in your business process, as shown in Figure
1, and hard-code the services bindings, which would make your process
rigid and less adaptable to change. If you look at the auto loan
procurement business process in Figure 1, you can see that there are
various points of variability involved in the process:
- Depending on the time of day, different endpoints
(CreditCheckService DayEP or CreditCheckServiceNightEP) need to be
invoked to provide the credit verification service.
- Depending on a customer's location (California or Texas),
different endpoints(LicenseVerificationCAEP or
LicenseVerificationNonCAEP) need to be invoked to provide the
license verification service.
- Depending upon the customer type (Gold or Silver),
different endpoints (LoanProviderGoldEP or LoanProviderSilverEP)
need to be invoked to provide the loan to the customer with
different response times.
As the number of service and process variability points starts to grow,
managing your business process using the approach described above becomes
tedious and reduces flexibility. Incorporating changes into the process
requires the developer to update and redeploy the business process. For
instance, suppose the auto loan business process now requires that you
need to serve a new category of customer, say Platinum, and that the
response time to serve the platinum customer should be faster than the
existing Gold and Silver customers. Incorporating this change requires
another if...else construct in the business process to invoke a particular
endpoint, say LoanProviderPlatinumEP, to satisfy the requirement, which
requires changing the business process and redeploying it. Without a
proper governance process in place, it's difficult to identify how this
change might impact your business process.
Extending the
Fabric core ontology model
In order to capture the points of variability in business policies and
provide the context information for a business service, Fabric allows you
to add capabilities (in the form of assertions)
to service endpoints through extensions to the core ontology model. For
instance, in the auto loan process, one of the aspects of context
information for customer type would be Gold, Silver or Platinum. Fabric
enables you to model your own extensions, load this context information
into Fabric, and create business policies to deliver dynamic capabilities
for your business service.
This rest of this article explains how to extend the core Fabric Model and
incorporate these capabilities. Figure 2 summarizes explains how various
Fabric modules interact with each other and with the business process.
Figure 2. A business
process enabled with dynamic binding and orchestration
Creating new assertions
Assertions are characteristics that describe the capabilities of an
endpoint. You can extend the industry ontology to add assertions that are
custom to your enterprise IT environment. At run-time, the WebSphere
Business Services Dynamic Assembler (hereafter called Dynamic Assembler)
uses these assertions to find the best-suited endpoint or service
realization for a consumer based on their business requirements. For more
information about assertions, refer to the
Websphere Business Services Fabric
Version 6.1 Information Center.
To implement the auto loan process, we'll extend the content-based
assertions defined in the Business Service Model, and build the following
two new assertions:
CustomerTypeAssertion
-
Description: Asserts the customer type that is supplied as part
of the loan request.
-
Point of variability : Customer type (Gold / Silver)
-
Assertion Type: Fabric => Assertions =>
ContentBasedAssertion
-
Use Case: Used by the Dynamic Assembler for endpoint selection.
Supplied as a part of the context, this assertion drives the Dynamic
Assembler to choose a particular loan provider service based on the
customer type.
-
Referenced Taxonomy: N/A
StateBasedAssertion
-
Description: Asserts a location that is supplied as part of the
loan request.
-
Point of variability : Customer's location (California or
Texas).
-
Assertion Type: Fabric => Assertions =>
ContentBasedAssertion
-
Use Case: Used by the Dynamic Assembler for endpoint selection.
Supplied as a part of the context, this assertion drives the Dynamic
Assembler to choose a particular license verification service
implementation based on the customer's location.
-
Referenced Taxonomy:N/A
We'll also use the Hours of Operation assertion, defined in the
Fabric core ontology model, which is used by the Dynamic Assembler to
select different endpoints depending on the time of the day. This
assertion takes care of the Time of day point of variability in our
business process. Depending on the time of the day , the appropriate
endpoint for credit verification will be invoked by the Dynamic Assembler.
As you can see, you can handle all the points of variability in the auto
loan process by leveraging the features of Fabric. Figure 3 shows the
simplified business process:
Figure 3. Simplified
business process
Building the
ontology extensions
Now let's look at how to model the assertions that we identified above
using the IBM Business Services Fabric Modeling Tool. The modeling tool is
available as a plug-in to Rational Software Architect, and is used for
extending the ontology.
Creating the glossary model
To create the glossary model, complete the following steps:
- Select File => New => Project => UML
Project to create a new UML modeling project.
- In the UML Modeling Project dialog, specify
AutoLoanExtensions as the Project
name, check Use default location, and check Create new
UML model in the project, as shown in Figure 4, then click
Next.
Figure 4. Create
the modeling project
- In the Create a New UML Model dialog, shown in Figure 5, specify
AutoLoanExtensionsModel as the File
name of the model, uncheck Create a default diagram in the new
model and click Finish?.
Figure 5. Create
the UML model
- Open the project and select the Details tab. Click Add
in the Applied Profiles section.
- In the Select Profile dialog, shown in Figure 6, select Profile in
Workspace and click Browse, then select
WBSFBusinessGlossaryProfile.epx, and click OK.
Figure 6. Add the
business blossary profile
- To create a package called glossary, which will hold the
required extensions, right-click AutoLoanExtensionsModel and
select Add UML => Package.
- Open the Main diagram by double-clicking Main under
Glossary.
- Right-click on Main diagram and select Add UML => Class,
and create a new class called StateBasedEnumeration.
- Open the Properties view for the StateBasedEnumeration class, and
select Stereotypes, then click Apply Stereotypes, as
shown in Figure 7.
Figure 7. Apply
stereotypes to the glossary package
- Check Glossary Term, then click OK, as shown in Figure
8.
Figure 8. Apply
stereotypes to the glossary package (2)
- In the same way, create a new class called
CustomerTypeEnumeration and apply the
Glossary Term stereotype.
Creating the ontology model
To create the ontology model, complete the following steps:
- As in the previous section, create a new UML project called
AutoLoanOntology that contains a UML model
called AutoLoanOntologyModel. Make sure to
uncheck the Create a default diagram in the new model option.
- Open the project and select the Details tab.
- In the Applied Profiles section, click Add.
- In the Select Profile dialog, shown in Figure 9, select Profile in
Workspace and click Browse, then select
WBSFOntologyProfile.epx, and click OK.
Figure 9. Add the
ontology profile
- Click Add in the Model Libraries section.
- Select XSDDataTypes as the Deployed Library, and click
OK, as shown in Figure 10.
Figure 10. Add
the XSD data type model library
- Select AutoLoanExtensionsModel and select Add UML =>
Package, then create a package called ontology.
- Apply the fabricNamespace stereotype to this package. as shown
in Figure 11.
Figure 11. Apply
stereotypes to the ontology package
- In the stereotype properties, as shown in Figure 12, specify
autoloan-assertions as the
directory, and as
http://www.ibm.com/autoloan/assertions as
the uri.
Figure 12.
Specify stereotype properties
Transforming the glossary terms
Next you need to transform the glossary terms you created, so that they can
be used as OWL classes in the ontology model. To do this, you need to
create a new glossary transformation configuration by completing the
following steps:
- Select Modeling =>Transform => New Configuration,
as shown in Figure 13.
Figure 13. Create
new glossary transform
- Select Fabric Transformations => Glossary
Transformation.
- Specify
AutoLoanGlossaryTransform as the
name, select AutoLoanOntology as the Configuration file
destination, and click Next, as shown in Figure 14.
Figure 14.
Specify glossary transformation information
- Select AutoLoanExtensionsModel as the source and
AutoLoanOntologyModel as the target, as shown in Figure 15,
then click Next.
Figure 15. Select
the source and target models
- Specify
ontology as the Target
Package, as shown in Figure 16, and click Finish.
Figure 16.
Specify the target package
- Run the transformation by selecting the transform icon as shown in
Figure 17. Notice the OWL class definitions created in the
AutoLoanOntologyModel project under the ontology package.
Figure 17. Run
the glossary transformation
Modeling
the ontology
Now you're ready to start building the ontology for the assertions.
- Open the Main diagram for the AutoLoanOntologyModel.
- Drag the StateBasedEnumeration and
CustomerTypeEnumeration OWL classes from the ontology package
onto the Main diagram
- Select Fabric - Model -Stubs => Models => Core
Ontology.
- Drag the Enumerated Value class onto the Main diagram.
- Create a Generalization directed from
StateBasedEnumeration to EnumeratedValue.
- Create a Generalization directed from
CustomerTypeEnumeration to EnumeratedValue.
- Create Instances for the following OWL classes:
| OWL Class | Enumeration Instance | Enumeration Instance Value |
|---|
| StateBasedEnumeration | StateBasedEnumerationInstance:CA | CA |
|---|
| StateBasedEnumeration | StateBasedEnumerationInstance:TX | TX |
|---|
| CustomerTypeEnumeration | CustomerTypeEnumerationInstance:Gold | Gold |
|---|
| CustomerTypeEnumeration | CustomerTypeEnumerationInstance:Silver | Silver |
|---|
We'll use these OWL class definitions to create our
assertions.
- Create a class called
StateBasedAssertion.
Apply the following stereotypes to this class. as shown in Figure 18:
-
fabricAssertion
-
owlClass
-
rdfs:label
Specify the rdfs:label as State
Based Assertion.
Figure 18. Apply
stereotypes to the StateBasedAssertion
- Expand the Fabric-Model-Stubs project and drag the
ContentBasedAssertion owlClass from the Policy Assertion
Ontology onto the Main diagram, as shown in Figure 19.
Figure 19. The
ContentBasedAssertion defined in the PolicyAssertionOntology
- Create a generalization directed from StateBasedAssertion to
ContentBasedAssertion.
- Add an attribute to the StateBasedAssertion class called
state of type
xsd:string.
- Apply the following stereotypes to the
state attribute, as shown in Figure 20:
-
fabricAssertedProperty
-
owl:DatatypeProperty
-
owl:FunctionalProperty
-
rdfs:label
Figure 20. Apply
stereotypes to the state attribute
- Scroll to the Stereotype Properties section and specify the
following. as shown in Figure 21:
-
assertionPropertyComparator:
EqualsComparator
-
controlWidget :
ReferenceSelect
-
label:
State
Figure 21.
Specify the stereotype properties for the state attribute
- Create a directed association from the StateBasedAssertion to
StateBasedEnumeration. Provide the label as state , and apply
the fabricEnumeratedProperty stereotype to it.
- Repeat steps 6-11 to create a CustomerTypeAssertion. Specify
Customer Type
Assertion
as the label for the assertions. Add the
customerType attribute to the class, with
the rdfs:label property as
Customer Type.
Figure 22 and 23 show the completed modeling diagram:
Figure 22. Completed
ontology model
Figure 23. Completed
ontology model (2)
Transform the
ontology model
Now you need to transform the ontology model that you created into the
actual OWL files by doing the following:
- Select Modelling => Transform =gt; New Configuration.
- Select Fabric Transformations => OWL Transformation.
- Specify
AutoLoanOntologyTransform as the
name, select OWL Transformation, and specify
/AutoLoanOntoloyt as the Configuration
file destination, then click Finish, as shown in Figure
24.
Figure 24.
Configure ontology transformation
- Select Auto Loan Ontology Model as both the source and target,
as shown in Figure 25, then click Finish.
Figure 25.
Specify the source and target models
- Run the transformation. The OWL transformation configuration runs the
transformation logic to produce the necessary OWL constructs. The
generated OWL file, shown in Figure 26, can be bundled as a Fabric
Content Pack archive, or FCA file, and imported into the Fabric
Governance Manager.
Figure 26. The
generated OWL file
Summary
This article described the use case and requirements of the composite
business process that you'll implement in the subsequent parts. You
learned about the business process's variability points and modeled those
variability points as ontology extensions to the IBM Business Service
Fabric Model using the Fabric Modeling tool. You now have a set of
metadata defining the points of variability in the business process.
Fabric can use this metadata for dynamic endpoint selection.
Downloads | Description | Name | Size | Download method |
|---|
| Project containing the model | AutoLoanModel.zip | 95KB | HTTP |
|---|
| Fabric content archive containing the assertions | AutoLoanAssertionsFCA.zip | 4KB | HTTP |
|---|
Resources -
Creating
flexible service-oriented business solutions with WebSphere Business Services Fabric, Part
1: Overview
(developerWorks 2007): Part 1 of this series describes the concepts of
business services and composite business services and how Business
Services Fabric provides an SOA platform to model, assemble, deploy,
manage and govern composite business services.
-
WebSphere business
process management zone:
Get the latest technical resources for WebSphere BPM solutions, including
articles, tutorials, events, downloads, and more.
-
Business Process Management
enabled by SOA:
Get complete product information on IBM BPM software, including features
and benefits, downloads, and more.
-
The
future of the Web is Semantic
(developerWorks 2005): Learn how organizations can leverage ontology-based
development.
-
OWL: Get more information on Web
Ontology Language.
-
WebSphere
Business Services Fabric product information:
Get product information, including features and prerequisites.
-
Service
Component Architecture (SCA):
Get information and the specification for SCA, a technology that
simplifies application development and implementation in an SOA.
-
WebSphere
Business Process Management Version 6.1 information center:
Get complete product documentation for WebSphere BPM products.
-
Getting Started with
IBM WebSphere Business Services Fabric V6.1:
This IBM Redbook provides a complete overview of Fabric, from an
architectural introduction, to an installation guide, and a step-by-step
scenario that describes how to model, assemble, deploy, and manage
composite business applications.
About the authors | 
| |
Naveen Balani works as an Software Architect on WebSphere
Business Services Fabric. He likes to research upcoming technologies and
is a regular contributor to IBM developerWorks, covering such topics as
Web services, ESB, JMS, SOA, architectures, open-source frameworks,
semantic Web, J2ME™, persuasive computing, the Spring series,
AJAX, and various IBM products. He is also a co-author of
Beginning
Spring Framework 2
(Wiley, 2008) and the IBM Redbook
Getting Started with IBM
WebSphere Business Services Fabric V6.1.
You can reach Naveen at
naveenbalani@rediffmail.com.
|
| 
| |
Rohit Sardesai works as a software engineer in the IBM India
Software Lab, in Mumbai. He is part of the IBM WebSphere Business Services
Fabric team. You can reach Rohit at
rohitsardesai@in.ibm.com. |
| 
| |
Ravikumar Vishwakarma is a software engineer in the IBM India
Software Lab, in Mumbai. He is part of the IBM Websphere Business Services
Fabric team. You can reach Ravikumar at
viraviku@in.ibm.com. |
| 
| |
Manoj Pal is a software engineer in the IBM India Software Lab, in
Mumbai. He is part of the IBM Websphere Business Services Fabric. You can
reach Manoj at
palmanojkumar@in.ibm.com. |
| 
| |
Matt Sanchez is an IBM Senior Technical Staff Member and Chief
Architect for WebSphere Business Services Fabric. Matt is responsible for
the architecture and technical direction of IBM’s industry SOA
accelerators, including WebSphere Business Services Fabric and the
Industry Content Packs. He works closely with technical leaders across IBM
and with clients to help shape the future of IBM's SOA products and
solutions. You can reach Matt at
msanchez@us.ibm.com.
|
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