OntoGrid Semantic Grid Tutorial Manchester, February 2007
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Transcript of OntoGrid Semantic Grid Tutorial Manchester, February 2007
OntoGrid Semantic Grid TutorialManchester, February 2007
Semantic Grid.Introduction
www.ontogrid.eu
Oscar CorchoUniversity of Manchester
2Oscar Corcho. OntoGrid Semantic Grid tutorial. February 2007
Outline
Background The Grid and its characteristicsOpen Grid Services Architecture-OGSA Grid Standardization ActivitiesSemantic Grid
OntoGrid and Semantic-OGSA (S-OGSA)The S-OGSA modelS-OGSA capabilities and mechanismsLifetime specification
S-OGSA scenarios of use Conclusions Agenda
3Oscar Corcho. OntoGrid Semantic Grid tutorial. February 2007
What is a Grid?
LicenseLicense
PrinterPrinter
A grid is a system consisting of Distributed but connected resources and Software and/or hardware that provides and manages logically
seamless access to those resources to meet desired objectives Infrastructure that will enable “coordinated resource sharing and
problem solving in dynamic, multi-institutional virtual organizations”
A grid is a system consisting of Distributed but connected resources and Software and/or hardware that provides and manages logically
seamless access to those resources to meet desired objectives Infrastructure that will enable “coordinated resource sharing and
problem solving in dynamic, multi-institutional virtual organizations”
R2AD
DatabaseDatabase
Webserver
Webserver
Data CenterCluster
Handheld Supercomputer
Workstation
Server
Adapted from Hiro Kishimoto (GGF17 opening keynote)
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Virtual Organizations
Dynamic confederations organized around common goals Diverse membership & capabilities
• People, compute resources, data resources, etc. Diverse geographic distribution
Sharing is well-controlled Minimum knowledge about physical characteristics of resources Construction of higher level capabilities via composition of existing ones
similar to SOA
From http://www.globus.org
°
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Grid & Related Paradigms
Utility Computing• Computing “services”• No knowledge of provider• Enabled by grid technology
Utility Computing• Computing “services”• No knowledge of provider• Enabled by grid technology
Distributed Computing• Loosely coupled• Heterogeneous• Single Administration
Distributed Computing• Loosely coupled• Heterogeneous• Single Administration
Cluster• Tightly coupled• Homogeneous• Cooperative working
Cluster• Tightly coupled• Homogeneous• Cooperative working
Grid Computing• Large scale• Cross-organizational• Geographical distribution• Distributed Management
Grid Computing• Large scale• Cross-organizational• Geographical distribution• Distributed Management
Source: Hiro Kishimoto (GGF17 opening keynote)
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Open Grid Service Architecture - OGSA
Cross cutting requirements Interoperable VO level Optimized Reliable Certain QoS Guarantee Scalable Available Extensible
Characteristics Service Orientation Management operations
• Resource Representation/ State
• Lifetimecreate
stop
destroy
queryProperties
rewind
Get/ set PropertiesTotal capacity
Service Resource
Available space
Used space
WS-RFWS-ManagementWS-I+WS-GAF
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The Open Grid Services Architecture
An open, service-oriented architecture (SOA)Resources as first-class entitiesDynamic service/resource creation and destruction
Built on a Web services infrastructure Resource virtualization at the core Build grids from small number of standards-based
componentsReplaceable, coarse-grainede.g. brokers
CustomizableSupport for dynamic, domain-specific content……within the same standardized framework
Hiro Kishimoto: Keynote GGF17
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Grid Reality
“Virtual Homogeneity”RealizationsOGSA - Vision
. . . .
. . . .
Heavy use of XML
Requires experts to install, configure and maintain
Not near the ambitious OGSA landscape in terms of cross-cut requirements
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“To realise the Next Generation Grid requires semantically rich information representation, the exploitation of knowledge, and
co-ordination and orchestration that is aware of context and task”
David Snelling, NextGRID, Fujitsu, OGF
Source: Carole Goble
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Semantic Grid. Motivation (II)
Organisations that manage large datasets have to find agreements on what terms mean
Data versus metadata: we need bindings between the data and the data structure
Malcolm AtkinsonUK eScience envoy
Making this change in the code would change the [implicit] semantics of this Globus service
Lisa ChildersGlobus Toolkit
Provenance in Taverna is stored in RDF and OWLWorkflow reuse
Stuart OwenmyGrid
Well-typed workflows can be annotated with semantic typesKepler can use keyword-based or ontology-based search
Data, metadata an ontology (NSF report)
Amarnath GuptaSan Diego Supercomputing Centre
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Don’t we have Semantics in the Grid already?
Its called metadata. Or vocabularies. Or glossaries. It’s the state properties of a
resource. Its in information services. And registries and catalogues. And configuration files. And policy definitions. And service level agreements. And file names. And file headers. And directory naming
conventions
And code libraries. And type systems. And schemas. And applications. And data formats. And best practice. And documentation. And workflows. And notification events And monitoring logs And embedded in XML tags … And even ontologies!
And protocols. And decision procedures.
Embedding and implicit meaning is the enemy of shareability and reuse in an open and decoupled
and collaborative environment.
Machine processable descriptions are
machine actionable descriptions
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In summary
Integration
Annotation
Integration
Inference
OWL
RDF(S)
RDF
XML
SWRL
Extensible metadata schemas that you don’t have to nail down
Controlled vocabularies
Data fusion
Expressive models
Model fusion
Source: Carole Goble
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Metadata Matters Particularly for the following activities:
Provenance Systems Configuration Policy representation and reconciliation Resource discovery
Using: Annotation
• Open, flexible and extensible self describing schemas “Let’s describe my data set, or the output format of this tool, that changes all the
time” Lightweight, referable, non-flat schemas Decoupled, interoperable systems, which resist to syntactic changes
• Global naming schemes Data integration
• Resource models• Policy models
Reasoning• Complex problems
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“The Semantic Grid is an extension of the current Grid in which information and services are given well-defined and explicitly represented meaning, so that it can be shared and used by humans and machines, better enabling computers and people to work in cooperation” D. De Roure, et. al
The Semantic Grid
Semantics in and on the Grid
• Web Sites– www.semanticgrid.org
– Setting up the www.semanticgridcafe.org
• GGF Semantic Grid Research Group (SEM-RG)– Mailing List: [email protected]
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CombeChem
Semantic Grid trajectory
Time
Efforts
Implicit Semantics1st generation
SRB
Implicit SemanticsOGSA generation
GGF Semantic Grid Research Group
Many workshops
Systematic Investigation Phase
Specific experimentsPart of the Architecture
Dagstuhl Seminar
Grid Resource Ontology
Semantic Grid workshops
Pioneering PhaseAd-hoc experiments, early
pioneers
Demonstration Phase
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From the pioneering phase to the systematic investigation phase
In the pioneering phase...Ontologies and their associated technologies are not completely
integrated in the Grid applications• They are used as in Semantic Web applications
But there are distinctive features of Grid applications• Distribution of resources• Scale• Resource management and state• ... (non exhaustive and non compulsory list)
In the systematic investigation phaseWe have to take these features into accountAnd incorporate semantics as another Grid resource
Our proposal is: S-OGSA
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Lots
Not much
Not much
Lots
Knowledge Discovery
Information linkingFlexible &
extensible metadataschemas
Decision making
Grid
Sem
anti
cs
VO mgt
Provenance
Resource discovery &
brokering
Ontology building
Workflow discovery and design
General language annotation
Configuration
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Outline
Background The Grid and its characteristicsOpen Grid Services Architecture-OGSA Grid Standardization ActivitiesSemantic Grid
OntoGrid and Semantic-OGSA (S-OGSA)The S-OGSA modelS-OGSA capabilities and mechanismsLifetime specification
S-OGSA scenarios of use Conclusions Agenda
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EU-STREP Project OntoGrid
Middleware for the Semantic GridMetadata Storage & Querying Ontology AccessAnnotation
• Data and provenance
• ServicesBusiness Process MonitoringNegotiationCoordination
Applications Insurance SettlementSatellite Image Quality
Analysis
SEMANTIC OGSACapabilites & Behaviors for
Semantic GridsPrincipled way of realization
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S-OGSA Design Principles
• Conceptual: reference architecture that can be applied to any grounding (WSRF, WS-Man, WS-I+, etc.)
• Parsimony: Architecture as lightweight as possible: minimise the impact on tooling, not dictate content
• Extensibility: Extensible and customisable as opposed to complete and generic architecture
• Diversity : Mixed ecosystem of Grid and Semantic Grid services. Semantics Ignorant, Semantics aware but incapable, Semantics aware and capable
• Uniformity: Everything is OGSA compliant. Our services are Grid services, knowledge and Metadata are Grid Resources.
• Multiform-Multiplicity: Any resource can have multiple descriptions and any description can be in different formalisms
• Enlightenment: Straightforward migration path
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S-OGSA
Semantic-OGSA (S-OGSA) is...Our proposed Semantic Grid reference architectureA low-impact extension of OGSA
• Mixed ecosystem of Grid and Semantic Grid servicesServices ignorant of semanticsServices aware of semantics but unable to process themServices aware of semantics and able to process (part of) them
• Everything is OGSA compliant
Defined by • Information model
New entities
• CapabilitesNew functionalities
• Mechanisms How it is delivered
Model
Capabilities Mechanisms
provide/consume
expose
use
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S-OGSA Model. Semantic Bindings
Model
MechanismsCapabilities
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METADATAas SemanticAnnotations
S-OGSA Model Example
Model
MechanismsCapabilities
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Optimization
Execution Management
Resourcemanagement
Data
Security
Information Management
Infrastructure Services
Application 1 Application N
OG
SA
Sem
antic
-OG
SA
Semantic Provisioning
Services
From OGSA to the S-OGSA
Ontology
ReasoningKno
wle
dge
Metadata
Annotation
Sem
antic
bin
ding
Semantic Provisioning Services
Model
MechanismsCapabilities
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Semantic ProvisioningService
Knowledge Resource
Grid Entity
Semantic Binding
Grid ServiceIs-a
0..m0..m
1..m1..m
Semantic aware Grid Service
consume
produce
0..m0..m
1..m1..m
uses
WebMDS
SAMLfile
DFDL file
JSDL file
Is-a
Knowledge Entity
Is-a
Ontology Service
Is-a
Reasoning Service
Semantic BindingProvisioning Service
Annotation Service
Metadata Service
Grid Resource
OGSA-DAI
CASIs-a Is-a
Is-a
Is-a
Knowledge Service
Is-a
Ontology
Rule set
Knowledge Semantic Grid Grid
S-OGSA Model and Capabilities. The complete picture
Model
MechanismsCapabilities
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OntoKit: An implementation of S-OGSA
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OntoKit: An implementation of S-OGSA
OntologyRole-based
AuthZ
Semantically Aware
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S-OGSA Patterns. Semantic-ignorant service
Lifetime
MetadataService
OntologyService
Service
ResourceMetadataSeekingClient
Properties
Others….
Access/Query MetadataRefers to
Resource props
Model
MechanismsCapabilities
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S-OGSA Patterns. Semantic Aware but Incapable Service
Lifetime
MetadataService
OntologyService
Service
ResourceMetadataSeekingClient
Properties
Others…
Access/Query Semantic Bindings
Refers to
Get Semantic Binding Pointers
2
1Resource
properties
Model
MechanismsCapabilities
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S-OGSA Patterns. Semantic Aware and Capable Service
Lifetime
MetadataService
Service
ResourceMetadataSeekingClient
Properties
Others…
Access/Query Semantic Bindings1Semantics
1.1
Farm out request
Semantic aware interface
OntologyService
Model
MechanismsCapabilities
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S-OGSA Grounding. Grid Ontology and S-OGSA Ontology
Grid OntologyCommon set of ontologies
to describe Grid entities (resources and services)
Based on work from UniGrids
Effort to be continued by OntoGridAvailable in OntoGrid’s
CVS
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S-OGSA Metadata Access/Management Protocols
SB Factory
Client
Semantic Binding
Metadata Query
SBSB
SB
create
Query w/o Inference, UpdateContent
Query( over unified view)
WS-RP: Get/Set/Query Properties
WS-Addressing: epr
RDFRDF
create
query
Inspect-props . . .
query
Semantic Binding Service Suite
WS-RL: Destroy , SetTerminationTime
WS-RL ++: archive
WS-Notif: Subscribe / Notify
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Semantic Binding Service. Lifetime Specification
What happens if... ...any or all of the Grid entities it refers to disappears?
• Instrument and planning files for satellites do not disappear
• Insurance contracts, cars, repair companies, etc., may disappear
...the Knowledge entities disappear or evolve?• Ontologies may change
... a SB is no longer available (its content is not useful any more)? • Damage claims: add witness reports, improve info about location,
create new hypothesis...
When do/should SBs become invalid? How often should this be checked?
What is the status of the content of a SB (e.g., content checked, stable, unchecked, etc.)?
Is a SB always active or can it be archived after a period of time? Satellite data that is not used after some time
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Semantic Binding Service. WS-SBResourceLifetime
Lifetime specification based on WS-ResourceLifetime
Extension with Resource properties (state) Updates Archive Notifications
Stable
Stale
GEchanged
KEchanged
Archived Deleted
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WS-SBResourceLifetime vs WS-ResourceLifetime
WS-SBResourceLifetime
- archive- setUpdateTime
WS-ResourceLifetime
- setTerminationTime- destroy
Basic Operations- createSemanticBinding (Factory)- addGridEntityReference/removeGridEntityReference- addKnowledgeEntityReference/removeKnowledgeEntityReference- getContent- updateSBContent- query- queryWithInference
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Notifications
Semantic Binding Service
WS-Notif.[state]
WS-Notif[lastModificationTime]
Client
Grid Entity
Knowledge Entity
Client Client
Query-RP [state]
subscribe subscribe
subscribe
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Outline
Background The Grid and its characteristicsOpen Grid Services Architecture-OGSA Grid Standardization ActivitiesSemantic Grid
OntoGrid and Semantic-OGSA (S-OGSA)The S-OGSA modelS-OGSA capabilities and mechanismsLifetime specification
S-OGSA scenarios of use Conclusions Agenda
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Satellite Use Case: Technical issues
SpaceSegment
Ground Segment
DMOP files
Product files
SATELLITE FILES:
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Satellite Use Case: Technical issues
Comparison between planning and product generation:
...Instr#n(RA_2)planning
DMOP_File#n(StartTime) DMOP_File#n(StopTime)
DMOP_File#(n+1)StartTime
DMOP#(n+1)_File(StopTime)
DMOP_er (ORBIT_NUMBER,ELAPSED_TIME)
Instr#1planning
DURATION
PRODUCT_FILEStart_time(SENSING_START)
PRODUCT_FILEStop_time(SENSING_STOP)
...
Instr#n(RA_2)ProductGeneration
RA2_CAL_1PStop_time(SENSING_STOP)
RA2_CAL_1PStart_time(SENSING_START)
PRODUCT_data_gap... ...
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Satellite Use Case: Deimos Integrated Prototype
WebDAV
WS-DAIOnt-RDF(S)
SatelliteDomain Ontology
Satellite FileWebDAV client
e.g. MS Windows Explorer HTTP PUT
Metadata Service
QUARC-SG client JSP
2
UTC2SecondsSoaplab
3
45
7
2
1
1
3
6
Convert time to canonical representation
Annotate file
Obtain ontology
Type metadata
Store
Query
Convert time to canonical representationInput
criteria
Copy satellite file
Metadata generation processMetadata querying process
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Namefile (Product):
RA2_MW__1PNPDK20060201_120535_000000062044_00424_20518_0349.N1"
Corresponds to:
Satellite Use Case: Technical issues
Satellite files: PRODUCT filename
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Satellite files: Annotated PRODUCT FILE [...] <rdf:Description rdf:about="http://protege.stanford.edu/kb#10605"> <rdf:type rdf:resource="http://protege.stanford.edu/kb#Product_file"/>
<NS0:file_name>"RA2_MW__1PNPDK20060201_120535_000044792044_00424_20518_0334.N1"</NS0:file_name>
<NS0:sensing_start rdf:datatype="http://www.w3.org/2001/XMLSchema#int">192110735</NS0:sensing_start> <NS0:sensing_stop rdf:datatype="http://www.w3.org/2001/XMLSchema#int">192115215</NS0:sensing_stop> <NS0:specific_product_header rdf:resource="http://protege.stanford.edu/kb#10608"/> </rdf:Description> <rdf:Description rdf:about='http://protege.stanford.edu/kb#10649'><NS0:file_name>"RA2_MW__1PNPDK20060202_160340_000058672044_00441_20535_0344.N1"</
NS0:file_name> <NS0:sensing_start rdf:datatype='http://www.w3.org/2001/XMLSchema#int'>192211420</NS0:sensing_start> <NS0:sensing_stop rdf:datatype='http://www.w3.org/2001/XMLSchema#int'>192217287</NS0:sensing_stop> <NS0:specific_product_header rdf:resource='http://protege.stanford.edu/kb#10652'/> </rdf:Description>[...]
Satellite Use Case: Technical issues
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Satellite Use Case: Technical issues
Satellite files: DMOP (PLANNING) FILES
FILE ; DMOP (generated by FOS Mission Planning System) RECORD fhr FILENAME="DMOP_SOF__VFOS20060124_103709_00000000_00001215_20060131_014048_20060202_035846.N1" DESTINATION="PDCC" PHASE_START=2 CYCLE_START=44 REL_START_ORBIT=404 ABS_START_ORBIT=20498
ENDRECORD fhr................................ RECORD dmop_er RECORD dmop_er_gen_part RECORD gen_event_params
EVENT_TYPE=RA2_MEA EVENT_ID="RA2_MEA_00000000002063" NB_EVENT_PR1=1 NB_EVENT_PR3=0 ORBIT_NUMBER=20521 ELAPSED_TIME=623635 DURATION=41627862 ENDRECORD gen_event_params ENDRECORD dmop_erENDLIST all_dmop_erENDFILE
RECORD ID
RECORD parameters
RECORD parameters corresponding to other
RECORD structure.
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Satellite Use Case: Technical issues
Satellite Ontology (General view)
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Satellite Use Case: Technical issues
Timeline Planning-Product Generation:
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Insurance Grid
Business values:• Value (cost reduction, billing)• Time to market / speed of implementation• Ahead of competitors• Fit within (human and technical) organization• Innovation drive
Solve existing problems:• Making processes more efficient with a new approach• (more) Reliable / Accepted• Proven / Cheaper • -> CarRepairGid
Solve problems that could not be solved before:• Lack of trust/ Unfamiliar• Politics • Technical / organizational limitations• -> CarFraudGrid
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Business Case 1: Car Repair Business Case
Context: Repair damaged carsNegotiation between insurance and repair company
• Speed, Price, Quality• Method of repair, Selection of material,Paint, Coalition
Now:negotiation by hand long term (yearly)
Challenge: Automated negotiation short term (every claim) Include SLA
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S-OGSA Scenario. Insurance settlement
WS-DAIOnt
Negotitation Service (Manager)
JobNegotiation client
1
2
Do Negotiation
Atlas
RDF
RDFRD
F
RDF
RDF
RDFRD
F
RDF
RDF
RDF
InsurranceCo DB
Motor Vahicles
Car Parts
Repair CO. 1 (Nego. Srvc. Contractor)
Repair CO. 2 (Nego. Srvc. Contractor)
Repair CO. 3 (Nego. Srvc. Contractor)
Job + ContractorList
Job
Job
Cfp
Cfp
Cfp
propose Offer
Refuse
proposeOffer
2
2
4
4
4
accept5
Reject5
WS-DAIOnt
Car Repair
DB
RDF
RDFRD
F
RDF
RDF
RDF
Car Repair
DB
3 calculatePrice
3 calculatePrice
3 calculatePrice
Retrieve public Job desc.
LegacydatabasesLegacy
databases
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Situation:• A lot of tricks to get money from insurance companies
Now:• Ad hoc manual techniques• Only pattern search on local or national scale• Most tricks found on accident
Challenge:• Automated fraud detection
Business Case 2:CarFraudGrid
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Car Fraud Business Case Motivation
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Conceptual Architecture
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Local Damage Report
DB
DB
I. Company B
RDF Query for similar cases
sql
Semantic Binding Service
Damage Report
Damage Report
Fraud Diagnosis Service
WS-DAIOnt
Car Fraud OntologyLocal Semantic Adapter
(Grid-KP or S-OGSA-DAI)
S. Case Info
S. Case Info
IC InfoIC Info
SuspiciousCase
SuspiciousCase Submit for fraud
detection
I. Company A
. . . .
Local Damage Report
DBI. Company C
Company C Semantic Data Access Service
sql
1
1
2
3
4
5Do diagnosis
6
decision
query
. . . .
Red Flag Detector
doc
RDF Query for similar cases
4
. . . .
Company BSemantic Data Access Service
CFG Technical Design
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Ontology-based Role-based Authorisation
Insurance Security scenario cast as role based Grid Access Control Scenario.
Role based Access Control Policy is:Good Reputation Drivers are allowed to ask for an insurance
policy. Bad Reputation ones are not. VO ontology based on
KaOS ontologies (Actors, Groups and Actions)Role definitons
• Extend ontology with domain-specific classes and properties• Define roles wrt these extensions
E.g., a blacklistedDriver is a driver that has had at least 3 accident claims in the past
E.g., a goodReputationDriver is a driver that has been insured at least by one trusted company and that has had at most 2 accident claims
The Access Control Function uses a DL classifier to obtain roles of a Subject.
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WS-DAIOnt
XACML_AuthZService(PDP)
CarFraudService (PEP)
XACML AuthZ Request
getInsurancePolicy
VO Ontology Class Hierarchy -RDFS
RDF
RDF
John Doe has had 2 distinct accidents
Role OpMapping
Pellet Reasoner
Obtain Semantic Bindings of John Doe
Obtain all classes that are subclass of ROLE
Classify John Doe wrt VO ont
Lookup whether the ROLE that is inferred permits or not
XACML AuthZ Response
1
2
3
4
5
6
7
Semantic BindingService
PIPProxy
PDPProxy
VO OntologyOWL
S-OGSA Scenario. Authorisation
8 Result or Exception
/C=GB/O=PERMIS/CN=User0
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WS-DAIOnt
XACML_AuthZService(PDP)
CarFraudService (PEP)
XACML AuthZ Request
getInsurancePolicy
VO Ontology Class Hierarchy -RDFS
RDF
RDF
John Doe has had 2 distinct accidents
Role OpMapping
Pellet Reasoner
Obtain Semantic Bindings of John Doe
Obtain all classes that are subclass of ROLE
Classify John Doe wrt VO ont
Lookup whether the ROLE that is inferred permits or not
XACML AuthZ Response
1
2
3
4
5
6
7
Semantic BindingService
PIPProxy
PDPProxy
VO OntologyOWL
S-OGSA Scenario. Authorisation
8 Result or Exception
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WS-DAIOnt
XACML_AuthZService(PDP)
CarFraudService (PEP)
XACML AuthZ Request
getInsurancePolicy
VO Ontology Class Hierarchy -RDFS
RDF
RDF
John Doe has had 2 distinct accidents
Role OpMapping
Pellet Reasoner
Obtain Semantic Bindings of John Doe
Obtain all classes that are subclass of ROLE
Classify John Doe wrt VO ont
Lookup whether the ROLE that is inferred permits or not
XACML AuthZ Response
1
2
3
4
5
6
7
Semantic BindingService
PIPProxy
PDPProxy
VO OntologyOWL
S-OGSA Scenario. Authorisation
8 Result or Exception
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WS-DAIOnt
XACML_AuthZService(PDP)
CarFraudService (PEP)
XACML AuthZ Request
getInsurancePolicy
VO Ontology Class Hierarchy -RDFS
RDF
RDF
John Doe has had 2 distinct accidents
Role OpMapping
Pellet Reasoner
Obtain Semantic Bindings of John Doe
Obtain all classes that are subclass of ROLE
Classify John Doe wrt VO ont
Lookup whether the ROLE that is inferred permits or not
XACML AuthZ Response
1
2
3
4
5
6
7
Semantic BindingService
PIPProxy
PDPProxy
VO OntologyOWL
S-OGSA Scenario. Authorisation
8 Result or Exception
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WS-DAIOnt
XACML_AuthZService(PDP)
CarFraudService (PEP)
XACML AuthZ Request
getInsurancePolicy
VO Ontology Class Hierarchy -RDFS
RDF
RDF
John Doe has had 2 distinct accidents
Role OpMapping
Pellet Reasoner
Obtain Semantic Bindings of John Doe
Obtain all classes that are subclass of ROLE
Classify John Doe wrt VO ont
Lookup whether the ROLE that is inferred permits or not
XACML AuthZ Response
1
2
3
4
5
6
7
Semantic BindingService
PIPProxy
PDPProxy
VO OntologyOWL
S-OGSA Scenario. Authorisation
8 Result or Exception
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WS-DAIOnt
XACML_AuthZService(PDP)
CarFraudService (PEP)
XACML AuthZ Request
getInsurancePolicy
VO Ontology Class Hierarchy -RDFS
RDF
RDF
John Doe has had 2 distinct accidents
Role OpMapping
Pellet Reasoner
Obtain Semantic Bindings of John Doe
Obtain all classes that are subclass of ROLE
Classify John Doe wrt VO ont
Lookup whether the ROLE that is inferred permits or not
XACML AuthZ Response
1
2
3
4
5
6
7
Semantic BindingService
PIPProxy
PDPProxy
VO OntologyOWL
S-OGSA Scenario. Authorisation
8 Result or Exception
Ignorant of semantics
Semantic aware and capable of processing semantics
Semantic provisioning services
Semantic aware but incapable of processing semantics
61Oscar Corcho. OntoGrid Semantic Grid tutorial. February 2007
Outline
Background The Grid and its characteristicsOpen Grid Services Architecture-OGSA Grid Standardization ActivitiesSemantic Grid
OntoGrid and Semantic-OGSA (S-OGSA)The S-OGSA modelS-OGSA capabilities and mechanismsLifetime specification
S-OGSA scenarios of use Conclusions Agenda
62Oscar Corcho. OntoGrid Semantic Grid tutorial. February 2007
Conclusions
A principled Semantic Grid reference architectureLow-impact extension of OGSAMixed ecosystem of Grid and Semantic Grid services
Ontology and metadata technology... ... can be used in Grid applications ... has to be adapted for its use in Grid environments
• Grid-compliant (provide Grid protocols, interfaces, etc.)• Grid-aware (use of Grid technology)
First use cases being deployedStill far from large-scale (production) deployment
63Oscar Corcho. OntoGrid Semantic Grid tutorial. February 2007
More information
Publications An overview of S-OGSA: a Reference Semantic Grid Architecture.
Corcho O, Alper P, Kotsiopoulos I, Missier P, Bechhofer S, Goble C. Journal of Web Semantics 4(2):102-115. June 2006
http://www.ontogrid.eu/. Deliverable D1.2v2
Source code http://www.ontogrid.eu/, For Downloading Distributions Access to CVS
Connection type: pserveruser: ontogridpassword: not neededHost: rpc262.cs.man.ac.ukPort: 2401Repository path: /local/ontogrid/cvsrootmodule: prototype
64Oscar Corcho. OntoGrid Semantic Grid tutorial. February 2007
Outline
Background The Grid and its characteristicsOpen Grid Services Architecture-OGSA Grid Standardization ActivitiesSemantic Grid
OntoGrid and Semantic-OGSA (S-OGSA)The S-OGSA modelS-OGSA capabilities and mechanismsLifetime specification
S-OGSA scenarios of use Conclusions Agenda
65Oscar Corcho. OntoGrid Semantic Grid tutorial. February 2007
Agenda
Semantic Grid middleware
Ontology access (WS-DAIOnt-RDF(S)• Focus on RDF(S)• Grid ontologies
Metadata management (Semantic Binding Service)
Future of Semantic GridService-Oriented Knowledge UtilitiesOngoing work on S-OGSA
66Oscar Corcho. OntoGrid Semantic Grid tutorial. February 2007
Questions
Thank you for your attention!
Questions?
Acknowledgements OntoGrid Consortium
• Pinar Alper, Ioannis Kotsiopoulos, Paolo Missier, Wei Xing, Ian Dunlop, Sean Bechhofer, Carole Goble
OntoGrid Semantic Grid TutorialManchester, February 2007
Semantic Grid.Introduction
www.ontogrid.eu
Oscar CorchoUniversity of Manchester