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Primer Taller en Grid Computing Universidad del Valle, Cali, Colombia January 2007

Semantic-OGSA. www.ontogrid.eu. Oscar Corcho University of Manchester. Primer Taller en Grid Computing Universidad del Valle, Cali, Colombia January 2007. Outline. OntoGrid and Semantic-OGSA (S-OGSA) The S-OGSA model S-OGSA capabilities and mechanisms Lifetime specification

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Primer Taller en Grid Computing Universidad del Valle, Cali, Colombia January 2007

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  1. Semantic-OGSA www.ontogrid.eu Oscar Corcho University of Manchester Primer Taller en Grid ComputingUniversidad del Valle, Cali, Colombia January 2007

  2. Outline • OntoGrid and Semantic-OGSA (S-OGSA) • The S-OGSA model • S-OGSA capabilities and mechanisms • Lifetime specification • S-OGSA scenarios of use • Semantic Provisioning Services • Conclusions and Future Work Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  3. EU-STREP Project OntoGrid • Middleware for the Semantic Grid • Metadata Storage & Querying • Ontology Access • Annotation • Data and provenance • Services • Business Process Monitoring • Negotiation and Coordination • SEMANTIC OGSA • Capabilites & Behaviors for Semantic Grids • Principled way of realization • Applications • Insurance Settlement • Satellite Image Quality Analysis And other applications being analysed Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  4. Semantic Grid trajectory CombeChem Demonstration Phase Efforts Systematic Investigation Phase Specific experiments Part of the Architecture Dagstuhl Seminar Grid Resource Ontology Semantic Grid workshops Pioneering Phase Ad-hoc experiments, early pioneers SRB GGF Semantic Grid Research Group Many workshops Implicit Semantics OGSA generation Implicit Semantics 1st generation Time Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  5. 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 phase • We have to take these features into account • And incorporate semantics as another Grid resource • Our proposal is: S-OGSA Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  6. 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 Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  7. S-OGSA • Semantic-OGSA (S-OGSA) is... • Our proposed Semantic Grid reference architecture • Alow-impact extension of OGSA • Mixed ecosystem of Grid and Semantic Grid services • Services ignorant of semantics • Services aware of semantics but unable to process them • Services aware of semantics and able to process (part of) them • Everything is OGSA compliant • Defined by • Information model • New entities • Capabilites • New functionalities • Mechanisms • How it is delivered Model provide/ consume expose Capabilities Mechanisms use Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  8. S-OGSA Model. Semantic Bindings Model Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007 Capabilities Mechanisms

  9. S-OGSA Model Example METADATAas Semantic Annotations Model Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007 Capabilities Mechanisms

  10. From OGSA to the S-OGSA Semantic Provisioning Services Semantic binding Knowledge Metadata Ontology Annotation Reasoning Application 1 Application N Security Optimization Data OGSA Execution Management Semantic-OGSA Semantic Provisioning Services Resource management Information Management Infrastructure Services Model Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007 Capabilities Mechanisms

  11. S-OGSA Model and Capabilities. The complete picture Is-a WebMDS Annotation Service Metadata Service Ontology Service OGSA-DAI Grid Service Semantic BindingProvisioning Service Knowledge Service Is-a Reasoning Service Is-a CAS Is-a Is-a Is-a Knowledge Entity Semantic ProvisioningService Grid Entity 1..m 1..m SAMLfile uses Ontology Is-a Is-a Semantic aware Grid Service Knowledge Resource Grid Resource DFDL file Rule set 1..m 1..m produce consume JSDL file 0..m 0..m Semantic Binding Model 0..m 0..m Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007 Capabilities Mechanisms Is-a Knowledge Semantic Grid Grid

  12. OntoKit: An implementation of S-OGSA Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  13. OntoKit: An implementation of S-OGSA Semantically Aware OntologyRole-basedAuthZ Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  14. S-OGSA Patterns. Semantic-ignorant service Ontology Service Metadata Service Refers to Access/Query Metadata Properties Lifetime Metadata Seeking Client Resource props Resource Others…. Service Model Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007 Capabilities Mechanisms

  15. S-OGSA Patterns. Semantic Aware but Incapable Service Ontology Service Metadata Service Access/Query Semantic Bindings Refers to 2 Properties Lifetime 1 Metadata Seeking Client Get Semantic Binding Pointers Resource properties Resource Service Others… Model Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007 Capabilities Mechanisms

  16. S-OGSA Patterns. Semantic Aware and Capable Service Ontology Service Metadata Service Farm out request 1.1 Properties Lifetime 1 Metadata Seeking Client Access/Query Semantic Bindings Semantics Resource Service Others… Semantic aware interface Model Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007 Capabilities Mechanisms

  17. S-OGSA Grounding. Grid Ontology and S-OGSA Ontology • Grid Ontology • Common set of ontologies to describe Grid entities (resources and services) • Based on work from UniGrids • Effort to be continued by OntoGrid • Available in OntoGrid’s CVS Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  18. S-OGSA Metadata Access/Management Protocols Semantic Binding Service Suite create SB Factory create WS-Addressing: epr SB Semantic Binding SB WS-RP: Get/Set/Query Properties query Client SB WS-Notif: Subscribe / Notify RDF Inspect-props . . . WS-RL: Destroy , SetTerminationTime WS-RL ++: archive Query w/o Inference, UpdateContent query Query( over unified view) Metadata Query Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  19. 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/shouldSBs 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 Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  20. Lifetime specification based on WS-ResourceLifetime Extension with Resource properties (state) Updates Archive Notifications SB Housekeeping service Semantic Binding Service. WS-SBResourceLifetime Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  21. WS-SBResourceLifetime vs WS-ResourceLifetime • Basic Operations • createSemanticBinding (Factory) • addGridEntityReference/removeGridEntityReference • addKnowledgeEntityReference/removeKnowledgeEntityReference • getContent • updateSBContent • query • queryWithInference • WS-SBResourceLifetime • archive • setUpdateTime • WS-ResourceLifetime • setTerminationTime • destroy Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  22. Update Notifications key key .............. .............. ................ .............. .............. .............. .............. ................ .............. .............. • From entities to Semantic Binding Properties Lifetime Polling of resource property [lastModificationTime] Resource props Resource Others…. Service Grid Entity SemanticBindingService EPR Properties Lifetime Resource props Resource Polling of resource property [lastModificationTime] Others…. Service Knowledge Entity Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  23. Update Notifications .............. .............. ................ .............. .............. .............. .............. ................ .............. .............. key key .............. .............. ................ .............. .............. .............. .............. ................ .............. .............. • Semantic Binding Update • Description: Updates in the content or in the state of a Semantic Binding • Message content: • updateTime • updateType [stateChange,contentChange] • newState [any of the ones defined in the state machine] • updateReason Check that SB content is still valid SBHouseKeepingService SemanticBindingService EPR MetadataService Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  24. Outline • Background • The Grid and its characteristics • Open Grid Services Architecture-OGSA • Grid Standardization Activities • Semantic Grid • OntoGrid and Semantic-OGSA (S-OGSA) • The S-OGSA model • S-OGSA capabilities and mechanisms • Lifetime specification • S-OGSA scenarios of use • Semantic Provisioning Services • Conclusions and Future Work Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  25. Satellite Use Case: Technical issues Space Segment Ground Segment SATELLITE FILES: DMOP files Product files Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  26. Satellite Use Case: Technical issues • Comparison between planning and product generation: DMOP_File#(n+1) StartTime DMOP#(n+1)_ File (StopTime) DMOP_File#n(StartTime) DMOP_File#n(StopTime) Instr#1 planning ... DMOP_er (ORBIT_NUMBER, ELAPSED_TIME) Instr#n (RA_2) planning DURATION ... Instr#n(RA_2) Product Generation ... ... PRODUCT_data_gap PRODUCT_FILE Start_time (SENSING_START) PRODUCT_FILE Stop_time (SENSING_STOP) RA2_CAL_1P Start_time (SENSING_START) RA2_CAL_1P Stop_time (SENSING_STOP) Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  27. Satellite Use Case: Deimos Integrated Prototype Satellite File 2 WebDAV client e.g. MS Windows Explorer WebDAV HTTP PUT Annotate file 3 1 Copy satellite file Convert time to canonical representation 5 4 UTC2Seconds Soaplab Obtain ontology 6 Type metadata Convert time to canonical representation Store 7 Input criteria 1 2 QUARC-SG client JSP 3 WS-DAIOnt-RDF(S) Metadata Service Query SatelliteDomain Ontology Metadata for annotation Metadata generation process Metadata querying process Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  28. Satellite Use Case: Technical issues RECORD ID RECORD parameters RECORD parameters corresponding to other RECORD structure. 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_er ENDLIST all_dmop_er ENDFILE Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  29. Satellite Use Case: Technical issues Satellite Ontology (General view) Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  30. Satellite Use Case: Technical issues Satellite Ontology (Hierarchies) Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  31. Satellite Use Case: Technical issues • Planning (DMOP) RECORD parameters Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  32. Satellite Use Case: Technical issues RECORD ID transformed to XML RECORD parameters transformed Not yet transformed RECORD parameters. Parameters NOT needed to be transformed at this moment Satellite files: XMLed DMOP (PLANNING) FILES <fhr> <!-- --> <FILENAME>"DMOP_SOF__VFOS20060124_103709_00000000_00001215_20060131_014048_20060202_035846.N1"</FILENAME> <DESTINATION>"PDCC"</DESTINATION> <PHASE_START>2</PHASE_START> <CYCLE_START>44</CYCLE_START> <REL_START_ORBIT>404</REL_START_ORBIT> <ABS_START_ORBIT>20498</ABS_START_ORBIT> <!-- --> </fhr> <!-- --> <!-- --> <!-- --> <!-- --> <!-- DMOP_ID="DMOP-060124103709" --> <!-- CYCLE_STOP=44 --> <!-- REL_STOP_ORBIT=433 --> <!-- ABS_STOP_ORBIT=20527 --> <!-- --> ............................ <EVENT_TYPE>GOM_PAU</EVENT_TYPE> <EVENT_ID>"GOM_PAU_00000000011446"</EVENT_ID> <NB_EVENT_PR1>1</NB_EVENT_PR1> <NB_EVENT_PR3>0</NB_EVENT_PR3> <ORBIT_NUMBER>20527</ORBIT_NUMBER> <ELAPSED_TIME>5970047</ELAPSED_TIME> <DURATION>65881</DURATION> </gen_event_params> <!-- PEP_ID="" --> <!-- PEP_SENSOR_REQ_ID="" --> </dmop_er_gen_part> <!-- PARAM_ID=1 --> <!-- LINE="" --> </dmop_er> </FILE> Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  33. Satellite Use Case: Technical issues Satellite files: Annotated DMOP (PLANNING) FILES <?xml version='1.0' encoding='ISO-8859-1'?><rdf:RDF xmlns:rdf='http://www.w3.org/1999/02/22-rdf-syntax-ns#' xmlns:rdfs='http://www.w3.org/2000/01/rdf-schema#' xmlns:NS0='http://protege.stanford.edu/kb#' > <rdf:Description rdf:about='http://protege.stanford.edu/kb#10822'> <rdf:type rdf:resource='http://protege.stanford.edu/kb#Instrument_mode'/> <NS0:instrument_mode_id>MS</NS0:instrument_mode_id> </rdf:Description> <rdf:Description rdf:about='http://protege.stanford.edu/kb#11224'> <rdf:type rdf:resource='http://protege.stanford.edu/kb#DMOP_ER'/> <NS0:event_id>&quot;GOM_OCC_00000000541299&quot;</NS0:event_id> <NS0:duration rdf:datatype='http://www.w3.org/2001/XMLSchema#int'>53000</NS0:duration> <NS0:orbit_number rdf:datatype='http://www.w3.org/2001/XMLSchema#int'>20552</NS0:orbit_number> <NS0:elapsed_time rdf:datatype='http://www.w3.org/2001/XMLSchema#int'>2452293</NS0:elapsed_time> <NS0:event_type rdf:resource='http://protege.stanford.edu/kb#10713'/> </rdf:Description> [...] Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  34. Satellite Use Case: Technical issues Parameters to be transformed Parameters NOT needed to be transformed at the moment Parameters to be transformed at this moment Satellite files • PRODUCT FILES PRODUCT="RA2_MW__1PNPDE20060131_231554_000061672044_00416_20510_0181.N1" PROC_STAGE=N REF_DOC="PO-RS-MDA-GS-2009_3/M " SENSING_START="31-JAN-2006 23:15:54.654195" SENSING_STOP="01-FEB-2006 00:58:41.702319" PHASE=2 CYCLE=+044 REL_ORBIT=+00416 ABS_ORBIT=+20510 STATE_VECTOR_TIME="31-JAN-2006 23:28:36.484942" DELTA_UT1=+.323875<s> X_POSITION=+6637305.306<m> Y_POSITION=-2700075.034<m> Z_POSITION=+0000000.000<m> X_VELOCITY=-0622.619862<m/s> Y_VELOCITY=-1507.628845<m/s> Z_VELOCITY=+7377.140620<m/s> PRODUCT_ERR=0 TOT_SIZE=+00000000000087159984<bytes> SPH_SIZE=+0000006975<bytes> NUM_DSD=+0000000019 DSD_SIZE=+0000000280<bytes> NUM_DATA_SETS=+0000000004 Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  35. Satellite Use Case: Technical issues Parameters NOT needed to be transformed at this moment. !!! FUTURE SCALABILITY IMPROVEMENT !! Satellite files: XMLed PRODUCT FILE <PRODUCT> "RA2_MW__1PNPDE20060131_231554_000061672044_00416_20510_0181.N1“ </PRODUCT> <PROC_STAGE>N</PROC_STAGE> <REF_DOC>"PO-RS-MDA-GS-2009_3/M "</REF_DOC> <!-- --> <ACQUISITION_STATION>"PDHS-E "</ACQUISITION_STATION> <PROC_CENTER>"PDHS-E"</PROC_CENTER> <PROC_TIME>"01-FEB-2006 01:22:48.232601"</PROC_TIME> <SOFTWARE_VER>"RA2/5.02 "</SOFTWARE_VER> <!-- --> <SENSING_START>"31-JAN-2006 23:15:54.654195"</SENSING_START> <SENSING_STOP>"01-FEB-2006 00:58:41.702319"</SENSING_STOP> <!-- PHASE=2 --> <!-- CYCLE=+044 --> <!-- REL_ORBIT=+00416 --> <!-- ABS_ORBIT=+20510 --> <!-- STATE_VECTOR_TIME="31-JAN-2006 23:28:36.484942" --> <!-- DELTA_UT1=+.323875<s> --> <!-- X_POSITION=+6637305.306<m> --> <!-- Y_POSITION=-2700075.034<m> --> <!-- Z_POSITION=+0000000.000<m> --> <!-- X_VELOCITY=-0622.619862<m/s> --> <!-- Y_VELOCITY=-1507.628845<m/s> --> <!-- Z_VELOCITY=+7377.140620<m/s> --> <PRODUCT_ERR>0</PRODUCT_ERR> <TOT_SIZE>+00000000000087159984<bytes></TOT_SIZE> <SPH_SIZE>+0000006975<bytes></SPH_SIZE> <NUM_DSD>+0000000019</NUM_DSD> <DSD_SIZE>+0000000280<bytes></DSD_SIZE> <NUM_DATA_SETS>+0000000004</NUM_DATA_SETS> <!-- --> Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  36. Satellite Use Case: Technical issues • Namefile (Product): RA2_MW__1PNPDK20060201_120535_000000062044_00424_20518_0349.N1" Corresponds to: Satellite files: PRODUCT filename Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  37. Satellite Use Case: Technical issues 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>&quot;RA2_MW__1PNPDK20060201_120535_000044792044_00424_20518_0334.N1&quot;</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>&quot;RA2_MW__1PNPDK20060202_160340_000058672044_00441_20535_0344.N1&quot;</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> [...] Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  38. Satellite Use Case: Technical issues Satellite files (Metadata Queries): // Use to get a proxy class for MetadataService private java.lang.String MetadataService_address = "http://195.134.67.205:8080/AtlasService/services/MetadataService"; public java.lang.String getMetadataServiceAddress() { return MetadataService_address; } […] public eu.ist.ontogrid.ontokit.MetadataService.MetadataService getMetadataService() throws javax.xml.rpc.ServiceException { java.net.URL endpoint; try { endpoint = new java.net.URL(MetadataService_address); } catch (java.net.MalformedURLException e) { throw new javax.xml.rpc.ServiceException(e); } return getMetadataService(endpoint); } […] public static void main(String[] args) { MetadataServiceProxy proxy = new MetadataServiceProxy(); String query1 ="SELECT X FROM {X}kb:instrument_mode_id{Y} WHERE Y=\"STB\" USING NAMESPACE kb=&http://protege.stanford.edu/kb#"; String query2 = "SELECT Z FROM {X}kb:plan_file_name{Y},{Y}kb:file_id{Z}, {Y}kb:start_time{T1}, {Y}kb:stop_time{T2} WHERE T1>192067200 AND T1< 197247599 OR T2 > 192067200 AND T2<197247599 USING NAMESPACE kb=&http://protege.stanford.edu/kb#"; try { System.out.println("submitting test query"); String result = proxy.query(query2); System.out.println(result); AtlasResultSet results = new AtlasResultSet(result); Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  39. Satellite Use Case: Technical issues • Timeline Planning-Product Generation: Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  40. 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 Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  41. Business Case 1: Car Repair Business Case • Context: • Repair damaged cars • Negotiation 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 Metadata for data integration Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  42. Data and resources scenarios Register Repair Co. contract at CarRepairGrid. Select Repair Companies for negotiation Metadata scenarios Calculate offer by a Repair Company (damage report) Judge Invoice sent by Repair Company Process management scenarios Multi issue negotiation between Repair Companies (repair) Multi issue negotiation between >3 insurance companies (Recovery) Services scenarios Provide Policy Information Check coverage Security scenarios Check client registration at insurance companies Check Car Theft- automatic check on car identity i.e. frame numbers and parts S-OGSA Scenario. Insurance settlement Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  43. S-OGSA Scenario. Insurance settlement Repair CO. 2 (Nego. Srvc.Contractor) Repair CO. 3 (Nego. Srvc.Contractor) Repair CO. 1 (Nego. Srvc.Contractor) Negotiation client 2 Cfp Job 4 Refuse 1 Do Negotiation calculatePrice 3 Job + Contractor List accept 5 Cfp Job 2 Retrieve public Job desc. Negotitation Service (Manager) propose Offer 4 calculatePrice 3 Reject 5 Job Cfp 2 WS-DAIOnt RDF RDF Offer RDF propose calculatePrice 4 3 InsurranceCo DB WS-DAIOnt Atlas RDF RDF RDF RDF RDF Legacydatabases Car Parts Legacydatabases Motor Vahicles Car Repair DB Car Repair DB Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  44. Business Case 2:CarFraudGrid • 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 Metadata for data integration Metadata for reasoning Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  45. Known trick: Berliner Model • Trick: • Buy damaged expensive car • Change some features • Have stolen cars have accidents with it • Claim money from insurance company of stolen car • Search for: • Similar cars combined with similar situations combined with similar participants • National / International scale Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  46. Car Fraud Business Case Motivation Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  47. Car Fraud Business Case Motivation Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  48. Conceptual Architecture Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  49. Suggested Approach: Use case Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

  50. Domain model • Every insurance company uses its own database/domain model. Every claim database contains in some form important data about: • * cars • * situation • To find evidence we will look in claim history based on the current claim. • We look at car for: Car • * brand, e.g. Peugeot • * model, e.g. 307 • * type, e.g. SW • * mileage • * license plate • * owner • * color • * chassisnumber • * constructionyear • * countryofregistration Situation • * place of damage (angle of impact) • * description of accident • * time of accident • * accident location • * price of damage • * damaged objects • * witnesses ? Primer Taller en Grid Computing. Universidad del Valle, Cali, Colombia. January 2007

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