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Industrial Ontologies Group University of Jyväskylä SmartResource: Utilizing Semantic Web Services to Monitor Industrial Resources Vagan Terziyan “Device”

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Presentation on theme: "Industrial Ontologies Group University of Jyväskylä SmartResource: Utilizing Semantic Web Services to Monitor Industrial Resources Vagan Terziyan “Device”"— Presentation transcript:

1 Industrial Ontologies Group University of Jyväskylä SmartResource: Utilizing Semantic Web Services to Monitor Industrial Resources Vagan Terziyan “Device” “Expert” “Service” XML Finland 2005, 8-9 March, 2005 "XML - the Enabling Technology for Integrating Business Processes" Pori, Finland

2 Our Congratulations for Dear Ladies

3 Our Team and Consortium University of Jyväskylä Industrial Ontologies Group (SmartResource) “Industrial Ontologies” Group: http://www.cs.jyu.fi/ai/OntoGroup/index.html

4 WIDER OBJECTIVE - to combine the emerging Semantic Web, Web Services, Peer-to-Peer, Machine Learning and Agent technologies for the development of a global and smart maintenance management environment, to provide Web-based support for the predictive maintenance of industrial devices by utilizing heterogeneous and interoperable Web resources, services and human experts

5 MAIN RESEARCH OBJECTIVE Our intention is to provide tools and solutions to make heterogeneous industrial resources (files, documents, services, devices, processes, systems, human experts, etc.) web-accessible, proactive and cooperative in a sense that they will be able to analyze their state independently from other systems or to order such analysis from remote experts or Web-services to be aware of own condition and to plan behavior towards effective and predictive maintenance. GUN G lobal U nderstanding e N vironment

6 GUN Concept: All GUN resources “understand” each other

7 On-line learning Smart Maintenance Environment “Devices with on-line data” “Experts” Maintenance“Services”exchange data Maintenance data exchange

8 SmartResource Infrastructure “Device”“Expert” “Service”RSCDF “Smart Message”- ?!

9 Resource Maintenance Lifecycle 56°C StatesSymptoms DiagnosesPrescriptions Measurement Data Warehousing Predictive Measurement Condition Monitoring Maintenance Diagnostics Treatment Planning Predictive Monitoring Conditions Warehousing Predictive Maintenance Prescriptions Warehousing Predictive Diagnostics Diagnoses Warehousing Resource (device, expert, service)History

10 “Expert” Network “Device” “Service” Diagnostic model “Expert” User interface Labelled data Labelled data Learning diagnostic results and querying sample Labelled data Querying diagnostic results Maintenance Networking Environment “Device” Network “Service” Network ”Adapter” “RSCD Alarm Service” Sensor data RSCDF data ”Adapter” Sensor data RSCDF data “Embedded Alarm Service” Local (Embedded) Platform ”Adapter” RSCDF data RSCDF data Remote Expert Platform ”Adapter” Learning process RSCDF data Remote Service Platform History data Resource Agent

11 Research and Development: Resource State/Condition Description Framework (RSCDF) based on Semantic Web and extension of RDF (Resource Description Framework) RSCDF adapters (wrappers) for devices, services and experts: - browsable devices - application-expert interface - RSCDF -enabled services 1. Adaptation Stage Define Semantic Web-based General Adaptation Framework (GAF) for unification of maintenance data and interoperability in maintenance system “Device”“Expert”“Service” RSCDF

12 Resource state/condition Description Framework (R SC DF)

13 R SC DF: Goal R SC DF R SC DF – unified representation format for resource state and condition semantic description (annotation). R SC DF is an extension to RDF, which introduces upper-ontology for describing such characteristics of resources as states and correspondent conditions in different contexts, dynamics of state changes, target conditions and historical data about previous states and conditions.

14 s s t s - sub property of the property - subclass of the class - sub property of the RDF property RDFS R SC DF-Schema s t t s t ResourceClass Statement Property s Container t t s SR_ContainerSR_Statement SR_Property SmartResource DeviceServiceExpert SmartMessageResourceAgent Transformation Condition Measurement Maintenance t t t t t Description t t t Time t s t*t* t*t* t - type of the class, s s ss s s s s s s ss s R SC DFS context d – SR_Statement r – SR_Container sr_StatementType d – SR_Statement r – SR_Property member d – SR_Container r – SR_Statement rdfs:member t predicate d – SR_Statement r – SR_Property rdf:predicate s s t s s t s s t s s t has_Container d – SmartResource r – SR_Container s - type of the rdfs:Class t*t* t QuantityValue s Time Ontology rdfs:member Transformation Ontology Measurement Ontology Condition Ontology Maintenance Ontology t t t t t t s t s Resource Ontology t s Non-numerical Value Ontology NumericalValue s t MeasurementUnit t t Measurement Units Ontology s value d – NumericalValue r – rdf:Literal rdf:value unit d – NumericalValue r – MeasurementUnit Environment t t TempMark sysTime d – Environment r – TempMark r – TempMark t Model t s s s t Model Ontology EnumerativeValue t s s

15 rscdfs: Context_SR_Container SR_Statement: statement context rscdfs: SR_Statement is a subclass of the rdf:Statement. It also describe a statement but has a very innovative and useful addition – Statement Context. Via trueInContext property an instance of the rscdfs: SR_Statement points on a context container of other contextual statements. rscdfs: SR_Statement rdfs: Resource rscdfs: SR_Property subject object predicate rdfs: Resource rscdfs:SR_Statement Container of a context rscdfs:SR_Statement … trueInContext rscdfs: Context_SR_Container rscdfs: SR_Statement domainrange rdf: Property type trueInContext Extension of the rdf:Statement to rscdfs:SR_Statement with a trueInContext property

16 context context A context of the subject property. A context of the subject property. rscdfs: PropertyContextContainer rscdfs: SR_Property domainrange rdf: Property type … rdfs: Class domainrange rscdfs: SR_Property type context context Extension of the rdf:Property to rscdfs:SR_Property with a Context property rscdfs: PropertyContextContainer Where rscdfs: PropertyContextContainer has the instances of the rscdfs: SR_Property class as a container members. SR_Property: property context

17 RSCDF_Schema: context influence xXx xXx some property some property </rscdfs:PropertyContextContainer> X1X1X1X1 … … domainrange context X2X2X2X2xXx rscdfs: SR_Statement … xXx subject object predicate rscdfs: Context_SR_Container trueInContext … rscdfs:SR_Statement Container of a context rscdfs:SR_Statement X1X1 X2X2 predicate As a rdfs: domain and rdfs: range properties, rscdfs: context property restricts a content of the rscdfs: SR_Statement context container ( rscdfs: ContextSR_Container). …a… Context tolerance range

18 Statement is a true statement just if the statement context is TRUE. Statement (about ”Service #1 sets diagnosis Emergency”) makes sense in context, that Model #1 was used, a diagnostic was based on State #1 of Device #1 in time t1. RDF R eification – RSCDF T rue I n C ontext Service #1 Emergency diagnosis trueInContext useModel inTime basedOn Model #1 t1 State #1 Environment hasTime Device #1 hasContainer Service #1 Emergency diagnosis Service #1 Model #1 hasContainer Environment t1 hasTime Device #1 State #1 hasContainer … T RUE I N C ONTEXT RDFReification RDF Reification

19 Multiple SmartResource History Source History max 9:00 9:30 14:00 15:00 max T Normal Temperature T < max Extreme Temperature T >= max t V V < min min < V < max V > max S1S1 S5S5 S4S4 S3S3 S2S2 S6S6 t1t1 t0t0 t2t2 t3t3 t4t4 t5t5 t6t6 t7t7 t8t8 t9t9 t 10 t 11 t 12 t 13 t 14 t 15 t 16 t 17

20 Multiple SmartResource History Time Aggregation max 9:00 9:30 14:00 15:00 max T Normal Temperature T < max Extreme Temperature T >= max t V V < min min < V < max V > max S1S1 S5S5 S4S4 S3S3 S2S2 S6S6 t1t1 t0t0 t2t2 t3t3 t4t4 t5t5 t6t6 t7t7 t8t8 t9t9 t 10 t 11 t 12 t 13 t 14 t 15 t 16 t 17 [t 0 ;t 2 ]

21 Multiple SmartResource History Time Aggregation max 9:00 9:30 14:00 15:00 max T Normal Temperature T < max Extreme Temperature T >= max t V V < min min < V < max V > max S1S1 S5S5 S4S4 S3S3 S2S2 S6S6 t2t2 t3t3 t4t4 t5t5 t6t6 t7t7 t8t8 t9t9 t 10 t 11 t 12 t 13 t 14 t 15 t 16 t 17 [t 0 ;t 2 ] [t 4 ;t 6 ] t0t0

22 Multiple SmartResource History Time Aggregation max 9:00 9:30 14:00 15:00 T Normal Temperature T < max Extreme Temperature T >= max t V V < min min < V < max V > max S1S1 S5S5 S4S4 S3S3 S2S2 S6S6 t2t2 t3t3 t4t4 t6t6 t7t7 t8t8 t9t9 t 10 t 11 t 12 t 13 t 14 t 15 t 16 t 17 [t 0 ;t 2 ] [t 4 ;t 6 ] max [t 7 ;t 10 ] max t0t0

23 Multiple SmartResource History Time Aggregation max 9:00 9:30 14:00 15:00 max T Normal Temperature T < max Extreme Temperature T >= max t V V < min min < V < max V > max S1S1 S5S5 S4S4 S3S3 S2S2 S6S6 t2t2 t3t3 t4t4 t6t6 t7t7 t 10 t 11 t 12 t 13 t 14 t 15 t 16 t 17 [t 0 ;t 2 ] [t 4 ;t 6 ] max [t 7 ;t 10 ][t 14 ;t 17 ] max t0t0

24 Multiple SmartResource History State Aggregation max 9:30 14:00 15:00 Normal Temperature T < max t V S1S1 S3S3 S2S2 max [t 2 ;t 3 ] [t 0 ;t 2 ]&[t 7 ;t 10 ]&[t 14 ;t 17 ] [t 4 ;t 6 ]&[t 11 ;t 12 ] Extreme Temperature T >= max 9:00 T V < min min < V < max V > max S5S5 S4S4 t1t1 t0t0 t2t2 t3t3 t4t4 t5t5 t6t6 t7t7 t8t8 t9t9 t 10 t 11 t 12 t 13 t 14 t 15 t 16 t 17 [t 6 ;t 7 ]&[t 13 ;t 14 ] [t 12 ;t 13 ] [t 3 ;t 4 ]&[t 10 ;t 11 ] S6S6

25 Multiple SmartResource History Diagnosis Aggregation max 8:00 10:00 14:00 15:00 max Normal Temperature T < max t V S1S1 S3S3 S2S2 V < min min < V < max V > max T S5S5 S4S4 t1t1 t0t0 t2t2 t3t3 t4t4 t5t5 t6t6 t7t7 t8t8 t9t9 t 10 t 11 t 12 t 13 t 14 t 15 t 16 t 17 S6S6 - Normality - Emergency [t 0 ;t 3 ]&[t 4 ;t 6 ]&[t 7 ;t 10 ]&[t 11 ;t 13 ]&[t 14 ;t 17 ] [t 3 ;t 4 ]&[t 6 ;t 7 ]&[t 10 ;t 11 ]&[t 13 ;t 14 ] Extreme Temperature T >= max

26 TransformationTransformation For the purpose to allow resource transformation, Transformation Ontology of the properties was included in R SC DF. Mostly (in general case) the containers are transformed to other containers, and they are connected to a resource. But at the same time a resource can be transformed without associating with other resource. It can be done during the temporal transformation or with a purpose to provide transformed resource for shared use. After the transformation the transformation SR_Statement should be added as a container context and context of each container member. sr_StatementType rscdfs:SR_Statement rdfs: Resource rscdfs: SR_Property subject object predicate rscdfs: SR_Property rscdfs: Transformation rscdfs:SR_Statement Statement#3 rscdfs:SR_Statement Statement#1 rscdfs: SR_Container rscdfs:SR_Container Container#3 context rdfs: Resource rscdfs:SR_Statement Statement#2 rscdfs: SR_Statement … Container rscdfs: SR_Statement Container rscdfs: SR_Statement sr_StatementType rscdfs: SR_Statement rdfs: Resource rscdfs: SR_Property subject object predicate rscdfs: SR_Property rscdfs:Description Kettle#1 rscdfs:Description has_Container rscdfs:SR_Container Container#4 rscdfs:SR_Statement Statement#2 rscdfs: SR_Container rscdfs:SR_Container Container#5 context rdfs: Resource Resource Ontology sr_StatementType rscdfs: SR_Statement rdfs: Resource rscdfs: SR_Property subject object predicate rscdfs: SR_Property rscdfs:Description Kettle#1 rscdfs:Description has_Container rscdfs:SR_Container Container#6 rscdfs:SR_Statement Statement#3 rscdfs: SR_Container rscdfs:SR_Container Container#7 context rdfs: Resource Resource Ontology member rscdfs: SR_Container context member Transformation Ontology rscdfs:Transformation TimeAggreg_S-S

27 SmartResource - “Device” Description sr_StatementType rscdfs: SR_Statement max min Kettle rdfs: Resource rscdfs: SR_Property subject object predicate rscdfs: SR_Property rscdfs: Description Kettle#1 rscdfs:Description has_Container rscdfs:SR_Container Container#1 rscdfs:SR_Statement Statement#1 rscdfs: SR_Container rscdfs:SR_Container Container#2 context rscdfs: SR_Statement member rscdfs: SR_Container rscdfs:SR_Container Container#3 context rscdfs:SR_Statement Statement#2 sr_StatementType rscdfs: SR_Property rscdfs: Time rscdfs: SR_Statement rscdfs:SR_Statement Statement#3 rscdfs: SR_Statement rscdfs:SR_Statement Statement#4 rscdfs: SR_Container rscdfs:SR_Container Container#4 rscdfs: SR_Container rscdfs:SR_Container Container#5 member context rscdfs: SR_Property rscdfs: Measurement sr_StatementType rdfs: Resource rscdf: SR_Property rdfs: Resource subject object predicate rdfs: Resource rscdfs: SR_Property rdfs: Resource subject object predicate rscdfs:Measuremenr temperature rdfs: Resource rscdf:Measuremenr volume Non-numerical Value Ontology max>V>min max Resource Ontology Kettle#1 Resource Ontology Kettle#1 Resource Ontology --- [t 1 ;t 2 ] Measurement Ontology rdfs: Resource Environment rscdfs: SR_Property rscdfs:Time sysTime rdfs: Resource object predicate subject Non-numerical Value Ontology rscdfs:TempMark TempMark#1

28 <!DOCTYPE rdf:RDF [ ]> ]><rdf:RDF xmlns:rdf="&rdf;“ xmlns:rdf="&rdf;“ xmlns:rdfs="&rdfs;" xmlns:rdfs="&rdfs;" xmlns:rscdfs="&rscdfs;" xmlns:rscdfs="&rscdfs;" xmlns:rd="&rd;" xmlns:rd="&rd;" xmlns:ontoMeasurement="&ontoMeasurement;“ xmlns:ontoMeasurement="&ontoMeasurement;“ xmlns:ontoCondition="&ontoCondition;" xmlns:ontoCondition="&ontoCondition;"> <rscdfs:Device rdf:about="&rd;iKettle1“ rdfs:comment="Kettle#1 is an instance of rscdfs:Device class“ rdfs:comment="Kettle#1 is an instance of rscdfs:Device class“ rdfs:label="Kettle"> rdfs:label="Kettle"></rscdfs:Device> <rscdfs:SR_Statement rdf:about="&rd;iSR_Statement1" rdfs:comment="Describes that resource has a container" rdfs:comment="Describes that resource has a container" rdfs:label="SR_Statement1"> rdfs:label="SR_Statement1"> </rscdfs:SR_Statement> <rscdfs:SR_Container rdf:about="&rd;iContainer1" rdfs:comment="Container of iKettle1" rdfs:comment="Container of iKettle1" rdfs:label="Container1"> rdfs:label="Container1"> </rscdfs:SR_Container> <rscdfs:SR_Container rdf:about="&rd;iContainer2" rdfs:comment="Contextual Container of iSR_Statement1" rdfs:comment="Contextual Container of iSR_Statement1" rdfs:label="Container2"> rdfs:label="Container2"> </rscdfs:SR_Container> <rscdfs:SR_Container rdf:about="&rd;iContainer3" rdfs:comment="Contextual Container of iSR_Statement2" rdfs:comment="Contextual Container of iSR_Statement2" rdfs:label="Container3"> rdfs:label="Container3"></rscdfs:SR_Container> <rscdfs:SR_Container rdf:about="&rd;iContainer4" rdfs:comment="Contextual Container of iSR_Statement4" rdfs:comment="Contextual Container of iSR_Statement4" rdfs:label="Container4"> rdfs:label="Container4"> </rscdfs:SR_Container> <rscdfs:SR_Container rdf:about="&rd;iContainer5" rdfs:comment="Contextual Container of iSR_Statement3" rdfs:comment="Contextual Container of iSR_Statement3" rdfs:label="Container5"> rdfs:label="Container5"> </rscdfs:SR_Container> SmartResource - “Device” Description

29 </rdf:RDF> <rscdfs:SR_Statement rdf:about="&rd;iSR_Statement2" rdfs:comment="Describes a time of environment" rdfs:comment="Describes a time of environment" rdfs:label="SR_Statement2"> rdfs:label="SR_Statement2"> </rscdfs:SR_Statement> <rscdfs:TempMark rdf:about="&rd;iTempMark1" rdfs:comment="Describes value of the time" rdfs:comment="Describes value of the time" rdfs:label="TempMark1"> rdfs:label="TempMark1"></rscdfs:TempMark> <rscdfs:EnumerativeValue rdf:about="&rd;iEnumerativeValue1" rdfs:comment="Describes value of the Kettle1 temperature" rdfs:comment="Describes value of the Kettle1 temperature" rdfs:label="EnumerativeValue1"> rdfs:label="EnumerativeValue1"></rscdfs:EnumerativeValue> <rscdfs:EnumerativeValue rdf:about="&rd;iEnumerativeValue2" rdfs:comment="Describes value of the Kettle1 volume" rdfs:comment="Describes value of the Kettle1 volume" rdfs:label="EnumerativeValue2"> rdfs:label="EnumerativeValue2"></rscdfs:EnumerativeValue> <rscdfs:SR_Statement rdf:about="&rd;iSR_Statement3" rdfs:comment="Describes a temperature measurement of Kettle1" rdfs:comment="Describes a temperature measurement of Kettle1" rdfs:label="SR_Statement3"> rdfs:label="SR_Statement3"> </rscdfs:SR_Statement> <rscdfs:SR_Statement rdf:about="&rd;iSR_Statement4" rdfs:comment="Describes a volume measurement of Kettle1" rdfs:comment="Describes a volume measurement of Kettle1" rdfs:label="SR_Statement4"> rdfs:label="SR_Statement4"> </rscdfs:SR_Statement>… SmartResource - “Device” Description

30 SmartResource - “Service” Description sr_StatementType rscdfs: SR_Statement rdfs: Resource rscdfs: SR_Property subject object predicate rscdfs: SR_Property rscdfs: Description NN_Service#1 rscdfs:Description has_Container rscdfs:SR_Container Container#6 rscdfs:SR_Statement Statement#5 rscdfs: SR_Container rscdfs:SR_Container Container#7 context rscdfs: SR_Statement member rscdfs: SR_Container rscdfs:SR_Container Container#8 context sr_StatementType rscdfs: SR_Property rscdfs: Time rscdfs: SR_Statement rscdfs:SR_Statement Statement#7 rscdfs: SR_Container rscdfs:SR_Container Container#9 member context rscdfs: SR_Property rscdfs: Condition sr_StatementType rdfs: Resource rscdfs: SR_Property rdfs: Resource subject object predicate rdfs: Resource rscdfs:Condition diagnosis Non-numerical Value Ontology normality Resource Ontology --- [t 3 ;t 4 ] Condition Ontology Diagnostic model Service: neural network NN_Service#1 sr_StatementType rscdfs: SR_Statement rdfs: Resource rscdfs: SR_Property subject object predicate rscdfs: SR_Property rscdfs:Description Kettle#1 rscdfs:Description has_Container rscdfs:SR_Container Container#1 rscdfs:SR_Statement Statement#1 rscdfs: SR_Container rscdfs:SR_Container Container#2 context rdfs: Resource Resource Ontology member max min rdfs: Resource Environment rscdfs: SR_Property rscdfs:Time sysTime rdfs: Resource object predicate subject rscdfs:TempMark TempMark#2 rscdfs:SR_Statement Statement#6 sr_StatementType rscdfs: SR_Statement rdfs: Resource rscdfs: SR_Property subject object predicate rscdfs: SR_Property rscdfs:Description rscdfs:Description has_Model rscdfs:SR_Container Container#10 rscdfs:SR_Statement Statement#8 rscdfs: SR_Container rscdfs:SR_Container Container#11 context rdfs: Resource Resource Ontology NN_Service#1 rscdfs: SR_Statement member rscdfs: SR_Property Model Ontology predicate rscdfs:SR_Statement Statement#9

31 <!DOCTYPE rdf:RDF [ ]> ]><rdf:RDF xmlns:rdf="&rdf;“ xmlns:rdf="&rdf;“ xmlns:rdfs="&rdfs;" xmlns:rdfs="&rdfs;" xmlns:rscdfs="&rscdfs;" xmlns:rscdfs="&rscdfs;" xmlns:rd="&rd;" xmlns:rd="&rd;" xmlns:ontoMeasurement="&ontoMeasurement;“ xmlns:ontoMeasurement="&ontoMeasurement;“ xmlns:ontoCondition="&ontoCondition;" xmlns:ontoCondition="&ontoCondition;"> … <rscdfs:Service rdf:about="&rd;iNN_Service1" rdfs:comment=" NN_Service#1 is an instance of rscdfs:Service class " rdfs:comment=" NN_Service#1 is an instance of rscdfs:Service class " rdfs:label="NN_Service"> rdfs:label="NN_Service"></rscdfs:Service> <rscdfs:SR_Statement rdf:about="&rd;iSR_Statement5" rdfs:comment="Describes that NN_Service1 has a container" rdfs:comment="Describes that NN_Service1 has a container" rdfs:label="SR_Statement5"> rdfs:label="SR_Statement5"> </rscdfs:SR_Statement> <rscdfs:SR_Container rdf:about="&rd;iContainer6" rdfs:comment="Container of iSR_Statement5" rdfs:comment="Container of iSR_Statement5" rdfs:label="Container6"> rdfs:label="Container6"> </rscdfs:SR_Container> <rscdfs:SR_Container rdf:about="&rd;iContainer7" rdfs:comment="Contextual Container of iSR_Statement5" rdfs:comment="Contextual Container of iSR_Statement5" rdfs:label="Container7"> rdfs:label="Container7"> </rscdfs:SR_Container> <rscdfs:SR_Container rdf:about="&rd;iContainer8" rdfs:comment="Contextual Container of iSR_Statement6" rdfs:comment="Contextual Container of iSR_Statement6" rdfs:label="Container8"> rdfs:label="Container8"></rscdfs:SR_Container> <rscdfs:SR_Container rdf:about="&rd;iContainer9" rdfs:comment="Contextual Container of iSR_Statement7" rdfs:comment="Contextual Container of iSR_Statement7" rdfs:label="Container9"> rdfs:label="Container9"> </rscdfs:SR_Container> SmartResource - “Service” Description

32 </rdf:RDF> <rscdfs:SR_Statement rdf:about="&rd;iSR_Statement6" rdfs:comment="Describes a time of environment" rdfs:comment="Describes a time of environment" rdfs:label="SR_Statement6"> rdfs:label="SR_Statement6"> </rscdfs:SR_Statement> <rscdfs:TempMark rdf:about="&rd;iTempMark2" rdfs:comment="Describes value of the time" rdfs:comment="Describes value of the time" rdfs:label="TempMark2"> rdfs:label="TempMark2"></rscdfs:TempMark> <rscdfs:SR_Statement rdf:about="&rd;iSR_Statement7" rdfs:comment="Describes a diagnosis that was determined by NN_Service1" rdfs:comment="Describes a diagnosis that was determined by NN_Service1" rdfs:label="SR_Statement7"> rdfs:label="SR_Statement7"> </rscdfs:SR_Statement> <rscdfs:EnumerativeValue rdf:about="&rd;iEnumerativeValue3" rdfs:comment="Describes value of the diagnosis by NN_Service1" rdfs:comment="Describes value of the diagnosis by NN_Service1" rdfs:label="EnumerativeValue3"> rdfs:label="EnumerativeValue3"></rscdfs:EnumerativeValue> <rscdfs:SR_Statement rdf:about="&rd;iSR_Statement8" rdfs:comment="Describes that NN_Service1 has a container(Model)" rdfs:comment="Describes that NN_Service1 has a container(Model)" rdfs:label="SR_Statement8"> rdfs:label="SR_Statement8"> </rscdfs:SR_Statement> <rscdfs:SR_Container rdf:about="&rd;iContainer10" rdfs:comment="Container of iSR_Statement8" rdfs:comment="Container of iSR_Statement8" rdfs:label="Container10"> rdfs:label="Container10"></rscdfs:SR_Container> <rscdfs:SR_Container rdf:about="&rd;iContainer11" rdfs:comment="Contextual Container of iSR_Statement8" rdfs:comment="Contextual Container of iSR_Statement8" rdfs:label="Container11"> rdfs:label="Container11"> </rscdfs:SR_Container> <rscdfs:SR_Statement rdf:about="&rd;iSR_Statement9" rdfs:comment="Describes that context of the container is a predicate (instance of the rscdfs:Model property)" rdfs:comment="Describes that context of the container is a predicate (instance of the rscdfs:Model property)" rdfs:label="SR_Statement9"> rdfs:label="SR_Statement9"> </rscdfs:SR_Statement> SmartResource - “Service” Description

33 RSCDF-Lite: Context Description Framework (CDF) (Khriyenko O., Terziyan V.)

34 CDF Statement

35 CDF Schema: Property definition

36 Context Tolerance Range in CDF

37 Definition of a Subproperty in CDF

38 Property-Subproperty Hierarchy in CDF

39 Context-Sensitive Descriptions in CDF

40 Probabilities in CDF

41 Significance of Contextual Properties

42 General Adaptation Framework (GAF)

43 Resource Adaptation Framework Semantic Resource Adaptation Frameworkis a generic ontology-based approach to design adapters for heterogeneous Web resources. Semantic Resource Adaptation Framework is a generic ontology-based approach to design adapters for heterogeneous Web resources. Semantic Resource Adapters suppose to “wrap” data retrieved from external resources with semantic templates and deliver semantically annotated data from outside to a resource stripping out semantic markup.

44 Resource Adaptation with JCA Application Server EJB collaborative logic (beans) Resource Adapter Container-component contract System Contract Bean JCA Other resource Other adapter A specific JCA-compatible adapter has to be designed for every resource, which is supposed to be maintained and plugged into a distributed Semantic Web enabled proactive maintenance system Application components (beans) have to be designed to implement the semantic adaptation logic

45 Semantic Adaptation Semantic Adaptation results into mapping from data encoded according to some data representation model to some other model; Data transformation involves format’s metadata (schemas) and transformation rules; Data representation standards, transformation rules, underlying models and appropriate ontologies constitute semantic adaptation. Model 1Model 2 Encoded Data adaptation Shared Domain Model

46 SmartResource Layered Cake of Specifications RscDF Schema for the maintenance domain XML as a basis for RDF, RDFS and document serialization RscDF document with encoded data RDF Specification as a language for data representation in an RscDF document RDFS contains ontological basis for RDF and RscDF OWL provides ontological extension for RDFS and RscDF Schema

47 General Adaptation Framework (GAF) - Template Ontology adaptation … … xXx Hierarchy of the classes Hierarchy of the properties Creation and using the Template Ontology for atomic elements (classes and properties) allows us generating whole template in rscdf format of an incoming source.

48 X1X1X1X1 X2X2X2X2 X3X3X3X3 X4X4X4X4 XML General Adaptation Framework (GAF) XML … … xXx Template composition and mapping rules Ontology of Templates

49 Two Stages of Adaptation … XML 1 XML 2 XML n XML 0 Based on Unified State/Condition Description XML Schema Syntactic Adaptation: XSLT-Transformation Semantic Adaptation: Based on Ontology of Templates and Mapping Rules General Adaptation Framework (GAF)

50 XML 0 Ontology of Templates and Mapping Rules General Adaptation Framework (GAF)

51 - Schema of General Adaptation R SC DF XML 0 DB 0 format (n) 0 XML i DB i format (n) i Semantic transformation layer Syntactic transformation layer

52 Ontology of Templates and Transformation Rules Protégé Screenshots General Adaptation Framework (GAF) Transformation rules taxonomy RSCDF model taxonomy XML model taxonomy RSCDF templates taxonomy

53 General Adaptation Framework (GAF) Sample of RscDF template as instance in ontology Ontology of Templates and Transformation Rules Protégé Screenshots

54 General Adaptation Framework (GAF) XML Schema represented in ontology Ontology of Templates and Transformation Rules Protégé Screenshots XML Schema for given case

55 General Adaptation Framework (GAF) Ontology of Templates and Transformation Rules Protégé Screenshots Template for RscDF description of state represented in ontology

56 GAF Infrastructure

57 Presentation scenario XML i message Generator XSLT Editor XSLT i XML i schema XML 0 schema Device Adapter Syntactic transformation XML i state Semantic transformation XML o state R SC DF state Joseki Service Adapter Resource Browser R SC DF Failure Particular PowerMaint Adapter XML/SOAP xsd Web Service WSDL SOAP message R SC DF learning sample RDQL request R SC DF sub History PowerMaint Device Expert Remote Diagnostics Service Maintenance Services (Expert Adapter) Device History

58 SmartResource prototype environment

59 Component Set JCA

60 Semantic Adapter to a Device  Specification of the KF-330 blow molding machine was used for simulation of the device data (7 device parameters);  Corresponding XML-schema and XML- generator have become more sophisticated;  Maintenance ontology has been extended by specific classes related to the machine.  These device data allowed deeper analysis of human adapter (data visualization),  … and better analysis of the Web Service learning process.

61 Semantic Adapter to a Web-Service Application Server EJB Container KNN-Service WSDD WSDL SOAP engine SOAP client LOMBOZ Service Adapter 2-stage transformation RDQL-templates Application Server Service Adapter  Learning algorithm (KNN-method) was wrapped by a web service container using Axis and Lomboz;  Service Adapter using generated SOAP-client simulates agent’s requests for learning and diagnostics;  For RscDF-XML transformations, Service Adapter uses approach of 2-stage transformation with RDQL-templates.

62 Semantic Adapter to a Human Expert Application Server Servlet EJB Container Servlet Device Agent Expert Agent States Expert Adapter 2-stage transformation UI-templates “Expert”JFreeChart Labels  Expert Adapter utilizes 2-stage transformation and User Interface Templates for flexible building of a specific human interface;  Human Expert is requested for a diagnostics via e-mail ;  As a user interface use case, JFreeChart Java package and HTML representation are used.

63 Presentation Environment Application Server EJB Container Expert Adapter Device Adapter Service Adapter Web Container Control servlet JSP Web Client Histories RscDF-repository Ontology

64 Presentation Environment

65 2. Proactivity Stage “Expert” “Service” Labelled data Diagnostic model Querying diagnostic results Labelled data Watching and querying diagnostic data Labelled data History data “Device” Querying data for learning Learning sample and Querying diagnostic results Simple remote diagnostics model with semantic- based communication, expert and diagnostic service with learning capabilities. Model is based on R SC DF/R GB DF resource platforms, which internal structure contains resource adapter, resource agent, R SC DF/R GB DF database, R SC DF/R GB DF tools; and which external structure contains agent communication models. Knowledge Transfer from Expert to Service

66 Adding agents to resources Designing agents to maintain R GB DF Engine resources (R GB DF Engine) Enabling resource proactive R GB DF - Lite behavior (R GB DF - Lite) Analysis of inter-agent communication scenarios service learning remote diagnostics Design of General Proactivity Framework, which will allow assignment and flexible management of resources’ proactivity based on utilization of the agent technology ”Adapter” “Expert” “Service” “Device” Resource Agent Smart Maintenance Environment Environment “Device”“Expert”“Service” Remote diagnostics Service learning and remote diagnostics Expert~Service Expert ~ Service Proactivity Stage Challenges Lite

67 RDF Evolution towards GUN

68 3. Networking Stage Development of P2P agent-communication system Resource Semantic Discovery Maintenance Data & Knowledge Integration Certification and credibility assessment of services Scenario: one device - many services Scenario: one service – many devices Resource-to-resource communication Model integration Development of a decentralized networked maintenance management environment

69 P2P networking - highly scalable - fault-tolerable - supports dynamic changes of network structure - supports dynamic changes of network structure - does not need administration - does not need administration Why to interact? 1. Resource summarizes “opinions” from multiple services; 2. Services “learns” from multiple teachers; 3. One service for multiple similar clients; 4. Resources exchange lists of services; 5. Services exchange lists of clients. - network of hubs

70 Learning and test sample. Querying diagnostic results. Integrating services “Service” “Device” Labelled data Learning sample Test sample “Service” Diagnostic model w1w1w1w1 w2w2w2w2 w3w3w3w3 w4w4w4w4 w5w5w5w5 Evaluation and Result integration mechanism … Labelled data Device will support service composition in form of ensembles using own models of service quality estimation. Service composition is made with goal of increasing diagnostic performance.

71 Integrating knowledge “Service” Diagnostic model …“Device” Labelled data “Device” “Device” …“Device” “Device” “Device” 1 n Device-specific diagnostic model Device Class-specific diagnostic model Service builds classification model; many techniques are possible, e.g.: own model for each device; one model from several devices of the same type (provides device experience exchange).

72 CertificationCertification Sure, there are security threats as in any open environment. Security is to be ensured using existing solutions for Internet environment. Existence of certification authorities is required in the network. Certificates gained by services and trust to the certificate issuer are factors that influence optimal service selection. The quality of service is evaluated by users as well. Sure, there are security threats as in any open environment. Security is to be ensured using existing solutions for Internet environment. Existence of certification authorities is required in the network. Certificates gained by services and trust to the certificate issuer are factors that influence optimal service selection. The quality of service is evaluated by users as well. 5 3 4 Certifying party Device Service 1 Service 2 Service 3 6 1 2 Own evaluations trust

73 Device-to-Device “opinion” exchange Device Device 1 Device 2 Service 1 Service 2 trust = 100 trust = 2 6 1 ? ? 4 8 Device will be able to derive service quality estimates basing on analysis of ”opinions” of other devices and trust to them. Service quality evaluations

74 Service-to- Service “model” exchange and integration Diagnostic models exchange Diagnostic models integration entails creation of a more complex model extension or a service with new diagnostic model

75 Achieved and Expected Results Service Interaction ”One device – many services” P2P environment that integrates many devices, many services, many human experts and supports: Discovery of necessary network components using their profiles Interaction ”One service – many devices” Adaptation of resources (devices, services, experts) to the Environment Support for services that are able to learrn Unification of maintenance data Research Results: RSCDF RGBDF Proactive Resources P2P Maintenance Research Results: RSCDF RGBDF Proactive Resources P2P Maintenance Resource Agent  

76 On-line learning Future of Smart Maintenance Environment “Devices with on-line data” “Experts”Maintenance exchange data Maintenance data exchange “Services” “ ” “ Human / patient with embedded medical sensors ” “ Doctor/ Expert ” “Medical Web Services” “Web Services for environmental diagnostics and prediction ” “Experts in environmental monitoring ” “ ” “ Environment with sensors ” “ Staff/students ” “ Staff/students with monitored organizational data ” “Web Services in organizational diagnostics and management ” “ Manager / Expert ” Objects under observation “Experts” “Services: image and video processing”

77 New partners …are warmly welcome!

78 Obtain More Information about SmartResource from: Head of SmartResource Industrial Consortium (Steering Committee Head) Dr. Jouni Pyötsiä, Metso Automation Oy. Jouni.Pyotsia@metso.comJouni.Pyotsia@metso.com, Tel.: 040-548-3544 SmartResource Contact Person Prof. Timo Tiihonen, Vice-Rector, University of Jyväskylä tiihonen@it.jyu.fitiihonen@it.jyu.fi, Tel.: 014-260-2741 SmartResource Project Leader Prof. Vagan Terziyan, Agora Center, University of Jyväskylä vagan@it.jyu.fivagan@it.jyu.fi, Tel.: 014-260-4618


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