enterprise architecture in soa: models and methodologies ralph hodgson ceo, topquadrant email:...
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Enterprise Architecture in SOA:Enterprise Architecture in SOA:Models and Methodologies Models and Methodologies
Ralph HodgsonRalph HodgsonCEO, TopQuadrant
email: [email protected]
blog: http://topquadrant.typepad.com/ralph_hodgson
May 23rd, 2005
Going Semantic
CoverageCoverage
Semantic technology
Enterprise architecture and semantic technology
Enterprise architecture maturity model
Capabilities of semantic enterprise architecture
The US Federal Enterprise Architecture (FEA) Case study - using OWL ontologies for FEA and agency extensions to FEA.
Introduction: Ralph HodgsonIntroduction: Ralph Hodgson
Object Technologist since 1982 Came to US in 1994 to help create IBM’s Object
Technology Practice Founding member of IBM’s Java and Emerging
Technology Practice and IBM’s Portal Practice Co-founder of TopQuadrant, Inc. in 2001
– Ontology development, solution envisioning and solution architecture for semantic web applications
Recent work:– NASA Space Engineering Ontologies and model-based life-
cycles– GSA for FEA-RMO ontologies– FEA extensions, DOD and DODAF ontologies
Introducing TopQuadrant:Introducing TopQuadrant:Consultants in Semantic TechnologyConsultants in Semantic Technology
Ontology Development and Solution Envisioning for
Semantic Web Applications
Semantic Technology for Enterprise Architecture
‘Get Ready for Semantic Web’
Training program – next dates:
June 27 – 30, Washington, DC
Semantic technology is about putting Ontologies to Semantic technology is about putting Ontologies to workwork
So, what is an ontology?– It is a run time model of information– Defined using constructs for:
Concepts – classesRelationships – properties (object and data)Rules – axioms and constraintsInstances of concepts – individuals (data)
Semantic web ontologies are defined using W3C standards: RDF/S and OWL
This is an OntologyThis is an Ontology
Ontologies are like and unlike other IT modelsOntologies are like and unlike other IT models
Like databases ontologies are used by applications at run time (queried and reasoned over) – Unlike databases, relationships are first-class constructs
Like object models ontologies describe classes and attributes (properties)– Unlike object models, ontologies are set-based
Like business rules they encode rules– Unlike business rules, ontologies organize rules using axioms
Like XML schemas they are native to the web (and are in fact serialized in XML)– Unlike XML schemas, ontologies are graphs not trees and
used for reasoning
Realizing a semantic solution:Realizing a semantic solution:Required ComponentsRequired Components
Triple Store:– Kowari, Oracle, RDFGateway™, Sesame
Query Engine:– RDFGateway, Cerebra, HP Jena
Inferencing Engine:– Cerebra™, OntoBroker, Pellet, Racer, …
Application Builder:– RDFGateway™, Haystack
Visualization:– K-Infinity™, GraphViz,
Ontology Builder:– Protégé, SWOOP, …
Content Acquirers:– Translators, Scripts, TopBraid™, Semagix Freedom™, …
Realizing a semantic solution:Realizing a semantic solution:Vertical Application PlatformsVertical Application Platforms
Knowledge and Content Management– Semagix– SemanTX Life Sciences– Siderian– Profium
Semantic Interoperability– Cerebra– OntoBroker– OntologyWorks
IT Management– Metallect– Unicorn Solutions
An Impressive list of vendors are adopting An Impressive list of vendors are adopting Semantic Web StandardsSemantic Web Standards
Adobe BT Cisco IBM Oracle SAP Software AG Verio …
Large Enterprises with Large Enterprises with Semantic Web Pilots in ProgressSemantic Web Pilots in Progress
Audi Daimler Chrysler GE GM HP Microsoft NASA Sun Time Warner US Customs US GSA Cisco …
Why is semantic technology relevant to Why is semantic technology relevant to Enterprise Architecture?Enterprise Architecture?
An EA is a model of an enterprise expressing how:– people in roles,– performing activities,– using capabilities,– provided by systems
and resources,– overcome challenges
and generate value– with measurable results
for realizing business goals
source of the plan:www.nzherald.co.nz/index.cfm?ObjectID=10007286,
http://media.apn.co.nz/webcontent/image/gif/districtplan.GIF
This is a “Knowledge Model”.
Semantic Web Technologies are about modeling knowledge
Ontology can express the relationships in the Ontology can express the relationships in the Enterprise ArchitectureEnterprise Architecture
Bridges the gaps between business, technology and IT
Makes Value Nets “Navigate-able”
Makes Capabilities “Knowledge-able”
Makes Components “Knowledge-able”
Uses Semantic-Enabled Collaborative Tools
Component knows:where it is used, how it is realized, what it depends on,its measures of effectiveness
Knowledge Model using Semantic TechnologyBehavior Model for inferencingFederated ArchitectureAnalytical ToolsDecision Support
Capability knows:why it exists,what enterprise activities need it used, what it depends on, its measures of effectiveness
“Line of Sight” across:extended enterprise business unitswithin business unitsto measures of effectiveness
“Connects the dots” across:Business, technology and IT models
Semantic Systems infer answers Semantic Systems infer answers from a knowledge basefrom a knowledge base
Who is using what systems to do what?
Systems
Capabilities
Activities
Intents
StakeholdersWhat do I depend on to be effective?
What outcomes does this activity support?
Data can come from a variety of sources. Semantic model merges and integrates.
Enterprise Architecture Maturity ModelEnterprise Architecture Maturity Model
4. Connections between different systems and tools are established.
Enterprise Architecture Maturity LevelsEnterprise Architecture Maturity Levels
Ad hoc
Standardized
Formal
Federated
Executable
1. No common reference framework. Possible use of case tools. Little commonality between descriptions produced by different people and/or groups.
2. Established methodology for describing architectures. Use of industry standard/custom framework. Methodology not fully supported and enforced by tools.
3. Methodology enforced by tools based on a “Reference architecture”. Multiple tools in use, but from different vendors with low levels of interoperability. Reference framework and architectural models cannot be readily queried.
5. Models are consultable by applications at run time. Knowledge about enterprise activities, systems & capabilities becomes a real time resource.
Enterprise Architecture CapabilitiesEnterprise Architecture Capabilities
Ad hoc
Standardized
Formal
Federated
Executable
Some sharing of architectural
ideas.
Document provisioning
Architectural models produced by different groups can be understood
more easily. Linkages can be described.
EA framework compliance
Architects can adhere to the framework. Improved productivity of architects as well as
improved fidelity of models.
“What-If” analysis, reports.Centralized IT governance
Architectural models are accessible across organizational contexts.
Information can be independently constructed, aggregated and made accessible to wide audiences.
Aggregation and exchange of data and metadata. Federated IT governance
Improved enterprise agility. Real-time decision support and re-configuration of capabilities. Models stay in-sync with the real world.
Adaptive enterprise capability management and service provisioning
Benefits
Capabilities
Enterprise Architecture TechnologiesEnterprise Architecture Technologies
Ad hoc
Standardized
Formal
Federated
Executable
Personal computers and office tools
Templates,spreadsheets
Case tools, taxonomies
XML data exchange, web-based
repositories, RDF/S
OWL, web
services, SWRL,
agents
The Evolution of the EA Solution SpaceThe Evolution of the EA Solution Space
TopSCAPE™ Semantic EA PlatformTopSCAPE™ Semantic EA Platform
FEA and BMMP
Ontology Models
Reason
er
SMA
Metadata Graph DB
SMAEA
Query Engine
Vis
ualizati
on
Cach
e
Tri
ple
Sto
re
Data AccessR
ep
ort
G
en
era
tor
Collab
ora
tio
n
Kn
ow
led
ge
Pro
vis
ion
ing
Serv
ices
TopSCAPE
Fed
era
tion
Content Manager
Sch
em
as
Con
ten
t
Tem
pla
tes
Access
Translators
Imp
ort
Exp
ort
Valid
ato
r
ESB
SMA
Popkin
MDF
CASE tools, eg:
Popkin
Imp
act
An
aly
zer
Sim
ula
tors
Tra
nsla
tors
Decis
ion
S
up
port
Bu
dg
et
Man
ag
er
Port
folio
Man
ag
er
Tools Services
Data Access
DS
L E
ng
ines
Imp
ort
Exp
ort
For people, it can answer questions like:– Who is using what business systems to do what?– Who is using what technologies and products to do what? – What systems and business processes will be affected if we
upgrade a software package?– What technologies are supporting a given business process?– Where components are being re-used or could be re-used?– Who can we partner with at our agency and other agencies?– How is our agency architecture aligned with the FEA?– How new technologies (ie; XML, Web, Security) are being
taken up at our agency and at other agencies? Are they mature enough for e-government?
– … For applications, using an SOA, it can provide “An
Active Enterprise Architecture”, that is “Consultable” “Executable”
What can a Semantic Enterprise Architecture do?What can a Semantic Enterprise Architecture do?
The power of semantic technology for EA: The power of semantic technology for EA: Revealing Knowledge through InferencingRevealing Knowledge through Inferencing
Application provides CapabilityCapability enables CapabilityCapability supports Activity
Activity realizes IntentIntent isGoalOf Mission
enables is a Transitive Propertyprovides isSubPropertyOf enablessupports isSubPropertyOf enables
Given a capability and how it enables others, we can infer what activities it supports, how it realizes intent and the goals of the mission
TivoliPolicyDirector provides AuthenticationAuthentication enables SecureAccess
SecureAccess supports MissionOperations
TivoliPolicyDirector enables MissionOperations
The power of semantic technology for EA: Achieving The power of semantic technology for EA: Achieving Aggregation through FederationAggregation through Federation
Enterprise Architecture is a “System of
Systems”
What else becomes possible once a What else becomes possible once a semantic foundation has been built?semantic foundation has been built?
• New value propositions and new categories of applications
• Examples:
– NASA: Semantic Simulation-Based Acquisition (SBA)
– NASA: Semantic Collaborative Engineering Environment
– NASA: Semantic Command and Control– Federal Government: Semantic FEA-RMO Registry
Semantic Simulation-Based AcquisitionSemantic Simulation-Based Acquisition
Assessment and Trades
At the front-end of the systems acquisition lifecycle:
Pro
posa
ls
Sco
pe A
nnota
te
Valid
ate
NEXiOM Models•feedback re. quality•feedback re. IDTs
•feedback re. relevancefor strategic planning,capital planning, risk
management and partnering
Discipline-Based Tooling
Decisions and recommendations for
improvement
Ontology-based
ProposalRepository
Proposal Assessment
Onto
logy-B
ase
d Im
port
C. Potential for reuse of technologies and components
A. Program area supported?
B. Assess performance, risk and cost across disciplines?
D. Synergies for partnering
Semantic Collaborative Environment ArchitectureSemantic Collaborative Environment Architecture
Platform Infrastructure
Workgroup Enablement
Virtual Project Room
Realtime Collaboration
Alerts
Member Awareness
Workspace
Social Networks
Meetings
Roles
Work Settings
Choreography
Artifacts
Application Sharing
Activities
Tools
Tools Registry
WhiteboardDecision Support
EditorsQuery Manager
Knowledge Enablement
Ontology Registry
ArchivalCase Library
CategorizationSearch
Graphics3D-Engine2D-Engine GIS
Event Management TimelinesCalendar
Semantic InfrastructureSemantic Engine
p2p Metadata ReplicatorRSS
Triple Store Remote Sync
Eclipse JXTA
JENA
Semantic Blogs
Semantic Command and Control:Semantic Command and Control:Conceptual ArchitectureConceptual Architecture
Collaborative Mission Control
Knowledge Base
Semantic Engine
SCCE Capabilities
Launch Data Bus
NASA Networks
NASA Grid
Semantic Federal Enterprise ArchitectureSemantic Federal Enterprise Architecture
Business Reference Model (BRM)• Lines of Business• Agencies, Customers, Partners
Service Component Reference Model (SRM)• Service Layers, Service Types• Components, Access and Delivery Channels
Technical Reference Model (TRM)• Service Component Interfaces, Interoperability• Technologies, Recommendations
Data Reference Model (DRM)• Business-focused data standardization • Cross-Agency Information exchanges
Performance Reference Model (PRM)
• Government-wide Performance Measures & Outcomes• Line of Business-Specific Performance Measures & Outcomes
Federal Enterprise Architecture (FEA)
Busin
ess-D
riven A
ppro
ach
(Citize
n-C
ente
red Fo
cus)
Com
ponent-B
ase
d A
rchite
cture
s
FEA-RMO: The FEA Reference Model OntologyFEA-RMO: The FEA Reference Model Ontology
In 2004, TopQuadrant were contracted by GSA to develop an ontology of the FEA
FEA-RMO is a modular framework:– FEA Core– FEA BRM– FEA PRM– FEA SRM– FEA TRM– FEA DRM– BRM – PRM Bridge
Agency extensions:– Agency template– DoD extensions (connections to DODAF)– FAA extensions
Using Ontologies,Using Ontologies,FEA-RMO delivers “Line of Sight”FEA-RMO delivers “Line of Sight”
fea: Mission
fea: intentOf
fea: Agency
fea:undertakesfea: SubFunction
fea: hasIntent
brm: allignedWith
fea: IT Initiative
srm: developstrm: Technology
fea: ValuePoint
srm: Component
srm: allignedWith
prm: providesValue
prm: recivesValue
prm: hasPerformance prm: Performance
prm:measuredBy
prm: OperationalizedMeasureme
ntIndicator
srm:accessedThrough
srm: runsOn
……
rdfs:subClassOf
rdfs:subPropertyOf
fea: Customerfea: Process
Other relationships
FEA RMO Component – partial viewFEA RMO Component – partial view
Towards “Executable EA”:Towards “Executable EA”:‘InformationExchange” in DODAF Ontology‘InformationExchange” in DODAF Ontology
An Envisioned Semantic FEA Solution:An Envisioned Semantic FEA Solution:OMB and Agency Budget Proposal SystemOMB and Agency Budget Proposal System
Identify Proposal
C. Potential for reuse of Technologies/Components
A. Business Area and LOB supported?
B. Number of proposals with same capabilities?
Provide Feedback
C. Risk management feedback
A. Quality and reuse-of and reuse-for opportunities
B. Strategy and capital planning feedback
D. Recommendations for improvement and partnering
Assess Proposal
C. Refine Potential for reuse of Technologies/Components
A. Assess scope and context
B. Validate proposal against FEA-RMO models
D. Synergies for partnering
Proposal Budget
Repository
Knowledge Base:
FEA-RMO
Proposal Metrics and
Policies
ProposedBusiness Case
Assessment down from 3 months to 7 weeks
Re-submit period up from 1 week to 6 weeks - allowing time for collaborations to be negotiated
Submission Feedback
Towards TopScape: Semantic FEA RegistryTowards TopScape: Semantic FEA Registry
Current CapabilitiesCurrent Capabilities
Agency-specific extensions– Replacements, additions, deletions while preserving
traceability
– Architected for interoperability
Component Registry, describing components:– Business process support according to the BRM and
the SRM
– Performance measurements according to the PRM
– Technology platforms and use according to the TRM
Merge, federation and query Analytics and reporting
Future WorkFuture Work
Completing FEA-RMO with revisions to DRM More reports, visual query Using Ontologies for a Semantic Enterprise
Service Bus– Applying FEA-RMO to service provisioning– Semantics-Driven translation between EDOC and
BPEL– Smart ESB
Using OWL-S for Services Composition and Composite Applications
Take-Away PointsTake-Away Points
Semantic Technology is here and now Growing number of vendors with different approaches,
capabilities and maturity – technology selection is key With the Semantic Web standards rich models (ontologies)
can be federated and re-used across applications Key capabilities are:
– Integration of disparate data sources– Application interoperability– Business – IT alignment– Knowledge Management – sharing, reuse, terminology
reconciliation – Service discovery and composition – Agile enterprise
Semantic modeling is not the same as object or data modeling, so skills need to be developed
and we are not aloneand we are not alone
WebServices Journal, Dec 2004,– “Was the Universal Service Registry a Dream?
A combination of the features in UDDI and RDF may just make the dream come true” by: Fred Hartman; Harris Reynolds, BEA
“… Combining the capabilities of the current state of UDDI with the capabilities of RDF and OWL promises to resurrect the quest for the Universal Service Registry…"
http://webservices.sys-con.com/read/47278.htm
April, 2005 interview with the chief architect of Software AG
– “We recently announced the first globally available information integration product (called Enterprise Information Integrator v2.1) to incorporate Semantic Web technology. So my expectation is that you will see us using three core sets of standards and specifications as key components of our technology strategy: XML, WS-* and the Semantic Web Standards such as OWL."
ReferencesReferences
BMMP Business Enterprise Architecture (BEA) March 31, 2005 Update– http://www.dod.mil/comptroller/bmmp/products/architec
ture/BEA_3_31_05/iwp/default.htm Dean Allemang, Irene Polikoff, Ralph Hodgson, Paul
Keller, Jason Duley and Paul Chang: “COVE – Collaborative Ontology Visualization and Evolution”, IEEE Aerospace Conference, Montana, 2005– http://www.aeroconf.org/aeroupload/finishedpdf/F1458_
2.pdf Jim Cockrell and Ralph Hodgson, “"Proposed Wire
Data Management System Improvements for Space Shuttle Orbiter Ground Operations“, 8th Joint NASA, FAA, DOD Conference on Aging Aircraft, Palm Springs, CA, 31st January – 3rd February 2005,– http://www.jcaa.us/AA_Conference2005/Wiring/Ses40/40
_1100_Cockrell.pdf TopQuadrant White Paper on FEA-RMO, 2/21/2005
– http://www.topquadrant.com/tq_ea_solutions.htm
Books on Semantic Technology - 1Books on Semantic Technology - 1
Dieter Fensel, Wolfgang Wahlster, Henry Lieberman, James Hendler (Eds.): “Spinning the Semantic Web: Bringing the World Wide Web to Its Full Potential”, MIT Press, 2002
John Davies, Dieter Fensel & Frank van Harmelen:, “Towards the Semantic WEB – Ontology Driven Knowledge Management”, John Wiley, 2002
Johan Hjelm, “Creating the Semantic Web with RDF”, John Wiley, 2001
Dieter Fensel: “Ontologies: A Silver Bullet for Knowledge Management and Electronic Commerce”, Springer Verlag, 2001
Sheller Powers, “Practical RDF”, O’Reilly, 2003
Michael C. Daconta, Leo J. Obrst, Kevin T. Smith: “The Semantic Web: A Guide to the Future of XML, Web Services, and Knowledge Management”, John Wiley, 2003
Vladimir Geroimenko (Editor), Chaomei Chen (Editor), “Visualizing the Semantic Web”, Springer-Verlag, 2003
M. Klein and B. Omelayenko (eds.), “Knowledge Transformation for the Semantic Web”, Vol. 95, Frontiers in Artificial Intelligence and Applications, IOS Press, 2003
Books on Semantic Technology - 2Books on Semantic Technology - 2
Thomas B. Passin, "Explorer's Guide to the Semantic Web", ISBN 1932394206, June 2004
Jeff Pollock and Ralph Hodgson,
"Adaptive Information: Improving Business Through Semantic Interoperability, Grid Computing, and Enterprise Integration“, John Wiley, September 2004
Grigoris Antoniou and Frank van Harmelen, “A Semantic Web Primer”, The MIT Press, April 2004
Lee W. Lacy, “OWL: Representing Information Using the Web Ontology Language”, Trafford Publishing, 2005
AnnexAnnex
Ontology-Based EA Registry: TopSCAPE-EAOntology-Based EA Registry: TopSCAPE-EAFEA and DOD extensionsFEA and DOD extensions
Select either FEA Ontology or Agency-Specific Ontologies
Service specifications with links to more details
Search over all models for concepts
Demonstration at www.topquadrant.com/EAworld/index.htm
TopSCAPE-EA:TopSCAPE-EA:Search Example – “Quality”Search Example – “Quality”
Search results show FEA path
Demonstration at www.topquadrant.com/EAworld/index.htm
TopSCAPE-EATopSCAPE-EAExample of DOD extensions to FEAExample of DOD extensions to FEA
Agency-specific extensions shown “green”
Hot links to TRM areas
Mapping Components to the FEA Models - 1Mapping Components to the FEA Models - 1
Available elements from merged reference models
Mapping Components to the FEA Models - 2Mapping Components to the FEA Models - 2
Mapping Components to the FEA Models - 3Mapping Components to the FEA Models - 3
EA Analyst – Extension ReportEA Analyst – Extension Report
EA Analyst – Comparison ReportEA Analyst – Comparison Report
EA Analyst – Initiatives ReportEA Analyst – Initiatives Report
Example of Exporting OWL: FAAExample of Exporting OWL: FAA
<?xml version="1.0" ?>
- <rdf:RDF xmlns:fea="http://www.osera.gov/owl/2004/11/fea/fea#" xmlns:srm="http://www.osera.gov/owl/2004/11/fea/srm#" xmlns:ns1="http://www.topquadrant.com/owl/2005/03/fea/faasrm#" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#" xmlns:owl="http://www.w3.org/2002/07/owl#">
- <owl:Ontology rdf:about="http://www.topquadrant.com/owl/2005/03/fea/faasrm">
<owl:imports rdf:resource="http://www.osera.gov/owl/2004/11/fea/srm" />
</owl:Ontology>
- <srm:BusinessComponentSystem rdf:about="http://www.topquadrant.com/owl/2005/03/fea/faasrm#AirTrafficCRU-X_System">
<fea:mnemonic rdf:datatype="http://www.w3.org/2001/XMLSchema#string">CRU-X</fea:mnemonic>
<srm:realizes rdf:resource="http://www.osera.gov/owl/2004/11/fea/srm#TimeReporting" />
<srm:usedBy rdf:resource="http://www.osera.gov/owl/2004/11/fea/brm#FederalAviationAdministration" />
<ns1:hasDeploymentStatus rdf:resource="http://www.topquadrant.com/owl/2005/03/fea/faasrm#CommissionedInitalDeployment" />
<rdfs:label rdf:datatype="http://www.w3.org/2001/XMLSchema#string">Air Traffic CRU-X System</rdfs:label>
</srm:BusinessComponentSystem>
…
…