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MWSAFMETEOR-SWebServiceAnnotationFramework M ETEOR-S W EB S ERVICE A NNOTATION F RAMEWORK (MWSAF) Abhijit Patil, Swapna Oundhakar, Amit Sheth, Kunal Verma.

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Presentation on theme: "MWSAFMETEOR-SWebServiceAnnotationFramework M ETEOR-S W EB S ERVICE A NNOTATION F RAMEWORK (MWSAF) Abhijit Patil, Swapna Oundhakar, Amit Sheth, Kunal Verma."— Presentation transcript:

1 MWSAFMETEOR-SWebServiceAnnotationFramework M ETEOR-S W EB S ERVICE A NNOTATION F RAMEWORK (MWSAF) Abhijit Patil, Swapna Oundhakar, Amit Sheth, Kunal Verma LSDIS Lab, Department of Computer Science, The University of Georgia

2 MWSAFMETEOR-SWebServiceAnnotationFramework Outline Introduction METEOR-S Project @ UGA SchemaGraph Architecture Matching algorithm Results Conclusions and Future Work

3 MWSAFMETEOR-SWebServiceAnnotationFramework Introduction Semantic Web Services Explicate semantics of the Web service provider Use existing domain ontologies to provide contextual normalization Challenges Finding relevant domain ontologies Finding appropriate concepts in the ontologies Need a tool for allowing semi-automatic annotation

4 MWSAFMETEOR-SWebServiceAnnotationFramework Semantic Web services Describe services with ontology based languages e.g. OWL-S Add semantics to existing Web service standards e.g. METEOR-S Common factor OWL-S Describe Web services using ontology based service description languages METEOR-S Add Semantics by adding annotations to service descriptions in WSDL Common Factor Relate Web service I/O parameters with Ontological concepts

5 MWSAFMETEOR-SWebServiceAnnotationFramework METEOR-S Web service Annotation Map Web services inputs and outputs data represented using XML schema to concepts in ontologies Annotate WSDL with Ontologies How ? Borrow from Schema matching Semantic disambiguation between terms in XML messages represented in WSDL and concepts in ontology Match XML schema elements from WSDL to ontological concepts

6 MWSAFMETEOR-SWebServiceAnnotationFramework METEOR-S Web Service Annotation Framework (MWSAF) Assumptions Domain is depicted by one or more domain ontologies A Web service may belong to one or more domains MWSAF Functionality Find the domain(s) of the Web service Annotate the Web service with one or more ontologies

7 MWSAFMETEOR-SWebServiceAnnotationFramework Outline Introduction METEOR-S Project @ UGA SchemaGraph Architecture Matching algorithm Results Conclusions and Future Work

8 MWSAFMETEOR-SWebServiceAnnotationFramework http://swp.semanticweb.orghttp://swp.semanticweb.org, http://lsdis.cs.uga.edu/proj/meteor/swp.htmhttp://lsdis.cs.uga.edu/proj/meteor/swp.htm METEOR-SMETEOR-S Project @ UGA METEOR-S exploits Workflow, Semantic Web, Web Services, and Simulation technologies to meet these challenges in a practical and standards based approach. Applying Semantics in Annotation, Quality of Service, Discovery, Composition, Execution of Web Services Adding semantics to different layers of Web services conceptual stack Use of ontologies to provide underpinning for information sharing and semantic interoperability

9 MWSAFMETEOR-SWebServiceAnnotationFramework Semantics in METEOR-S and WS stack Publication Discovery Description Messaging Network Flow MWSDI: Scalable Infrastructure of Registries for Semantic publication and discovery of Web Services MWSAF: Semantic Annotation of WSDL (WSDL-S) MWSCF: Semantic Web Process Composition Framework METEOR-S at the LSDIS Lab exploits Workflow, Semantic Web, Web Services, and Simulation technologies to meet these challenges in a practical and standards based approach http://swp.semanticweb.orghttp://swp.semanticweb.org, http://lsdis.cs.uga.edu/proj/meteor/swp.htmhttp://lsdis.cs.uga.edu/proj/meteor/swp.htm

10 MWSAFMETEOR-SWebServiceAnnotationFramework METEOR-S – Types of Semantics Data / Information Semantics What – Formal definition of data in input and output messages of a web service Why – For Discovery and Interoperability How – By annotating input/output data of web services using ontologies Functional Semantics What – Formally representing capabilities of web service Why – For Discovery and Composition of Web Services How – By annotating operations of Web Services as well as provide preconditions and postconditions

11 MWSAFMETEOR-SWebServiceAnnotationFramework METEOR-S: 4 types of Semantics Execution Semantics What – Formally representing the execution or flow of services in a process or operations in a service Why – For Analysis (verification), Validation (simulation) and Execution (exception handling) of the process models How – Using State Machines, Petri nets, activity diagrams etc. QoS Semantics What – Formally describing operational metrics of a web service/process Why – To select the most suitable service to carry out an activity in a process How – Using QoS model [Cardoso and Sheth, 2002] for web services

12 MWSAFMETEOR-SWebServiceAnnotationFramework METEOR-S Architecture

13 MWSAFMETEOR-SWebServiceAnnotationFramework WSDL-S Metamodel

14 MWSAFMETEOR-SWebServiceAnnotationFramework WSDL-S P. Rajasekaran, J. Miller, K. Verma, A. Sheth, Enhancing Web Services Description and Discovery to Facilitate Composition, available at http://lsdis.cs.uga.edu/lib/download/swswpc04.dochttp://lsdis.cs.uga.edu/lib/download/swswpc04.doc

15 MWSAFMETEOR-SWebServiceAnnotationFramework Outline Introduction METEOR-S Project @ UGA SchemaGraph Architecture Matching algorithm Results Conclusions and Future Work

16 MWSAFMETEOR-SWebServiceAnnotationFramework Matching Issues (WSDL and Ontologies) Expressiveness Different reasons behind their development XML Schema used in WSDL for providing basic structure to data exchanged by Web services Ontologies are developed to capture real world knowledge and domain theory Knowledge captured XML Schema has minimal containment relationship Language used to describe ontologies model real world entities as classes, their properties and provides named relationships between them Solution Use hueristics to create normalized representation We call it SchemaGraph

17 MWSAFMETEOR-SWebServiceAnnotationFramework MWSAF – SchemaGraph What is SchemaGraph ? Normalized representation to capture XML Schema and DAML Ontology How to use SchemaGraph Conversion functions convert both XML Schema and Ontology to SchemaGraph representation XML schema used by WSDL W = {wc 1, wc 2, wc 3, …, wc n } where, wc i is an element in XML schema and n is the number of elements Ontology O = {oc 1, oc 2, oc 3, …, oc m } where, oc i is a concept in Ontology and m is the number of concepts Match function takes both W and O and returns a set of mappings

18 MWSAFMETEOR-SWebServiceAnnotationFramework MWSAF – XML Schema to SchemaGraph RuleXML Schema constructsSchemaGraph representation 1 Element,Node 2 simpleTypeNode 3 Enumeration values defined for simpleType S Node with edge between simpleType S node and value node with name hasValue 4 ComplexTypeNode 5 Sub-elements of complexType C which have range as basic XML datatypes Node with edge between complexType C node and this node with name hasElement 6 Sub-elements of complexType C which have range as complexTypes or simpleTypes or elements defined in same schema Edge between complexType C node and the range type node

19 MWSAFMETEOR-SWebServiceAnnotationFramework MWSAF – XML Schema to SchemaGraph - - - - WeatherReport Wind Phenomenon Directiongust_speed PhenomenonType PhenomenonIntensity MISTFOGSNOWDUST phenomena wind prevailing_direction hasElement intensity type hasValue Rule 3 Rule 1 simpletype => Node Rule 1 complextype => Node Rule 6 Rule 5 Rule 1 Element => Node

20 MWSAFMETEOR-SWebServiceAnnotationFramework MWSAF - Ontology to SchemaGraph RuleOntology representationSchemaGraph representation 1 ClassNode 2 Property of class D with basic datatype as range (Attribute) Node with edge joining it to class D node with name hasProperty 3 Property of class D with other class R as range (Relation) Edge between class D node and range class R node 4 Instance of class CNode with edge joining class C node to instance node with name hasInstance 5 Class(X)-subclass(Y) relationship Edge between class X node and class Y node with name hasSubclass

21 MWSAFMETEOR-SWebServiceAnnotationFramework MWSAF - Ontology to SchemaGraph - Superclass for all weather events Weather event - - - - - - - - - - - - WeatherPhenomenon CurrentWeatherPhenomenon WindEvent GustingWindEvent windDirection ObsucurationEvent PrecipitationEvent OtherWeatherPhenomenon Duststorm SnowMistFog SolidPrecipitationEvent Rule 1 Rule 2 Rule 5

22 MWSAFMETEOR-SWebServiceAnnotationFramework Outline Introduction METEOR-S Project @ UGA SchemaGraph Architecture Matching algorithm Results Conclusions and Future Work

23 MWSAFMETEOR-SWebServiceAnnotationFramework MWSAF – Architecture Ontology Store Categorize in domains Currently supports DAML and RDF formats Will be replaced in future with high quality ontology search mechanisms Parser Library Parser used to generate SchemaGraphs Currently provides Ontology2Graph and WSDL2Graph parsers Matcher Library Provides two types of Matching algorithms Element level Matching algorithms – NGram, CheckSynonyms, CheckAbbreviations, TokenMatcher Schema Matching algorithms Allows to add new Algorithms User Interface Displays the mappings and allows user to accept or reject it It also allows to match the concepts manually Displays the WSDL and ontology in tree format

24 MWSAFMETEOR-SWebServiceAnnotationFramework Ontology Store Parser Library Ont2Schema WSDL2Schema Matcher Library findMappings NGram MatchSynonyms CheckAbbreviations getBestMapping (Ranking algorithm) WSDL ConceptOntology ConceptMatch Score PhenomenonWeatherEvent0.51 windEventWind0.79 User provided WSDL File SchemaGraph For Ontology SchemaGraph For WSDL MWSAF – Architecture Annotated WSDL file

25 MWSAFMETEOR-SWebServiceAnnotationFramework Outline Introduction METEOR-S Project @ UGA SchemaGraph Architecture Matching algorithm Results Conclusions and Future Work

26 MWSAFMETEOR-SWebServiceAnnotationFramework FUNCTION findMapping INPUT wc i Є W, oc i Є O OUTPUT m i = ( wc i, oc i, MS ) MWSAF – Matching two concepts IOParametersMatch (w,o) = ElemMatch (w,o) + SchemaMatch (w,o) ElemMatch (w,o) => Element level match SchemaMatch (w,o) => Schema level match subTree(w) == subTree(o)

27 MWSAFMETEOR-SWebServiceAnnotationFramework MWSAF – Element level Match Definition Element level match is the measure of the linguistic similarity between two concepts based on their names. Assumption – Concepts from XML schema and ontology have meaningful names ElemMatch (w,o) => Element level match NameMatch with stemming SynonymsMatch : Snow and snowFall mean the same HypernymRelation (w is a kind of o) : prevailing_speed is a type of speed of a wind i.e. windSpeed HyponymRelation (o is a kind of w) Acronyms : Sea Level Pressure has acronym SLP

28 MWSAFMETEOR-SWebServiceAnnotationFramework WindEvent windSpeed WeatherEvent windDirection PressureEvent AltimeterSettingwindGustSpeed SeaLevelPressure PressureChangeEvent Class Property Ontology : weather-ont.daml WSDL : GlobalWeather.wsdl 0.756 0.69 0.9 0.5 0.8 0.23 1.0 MWSAF – Element level Match (example)

29 MWSAFMETEOR-SWebServiceAnnotationFramework MWSAF – Element level Match Element level match algorithms used by MWSAF NGram – This algorithms calculates similarity between two strings by considering the number of qgrams that they have in common. It uses dice coefficient to calculate this similarity. CheckSynonyms – This algorithm uses WordNet to find synonyms. It also accounts for hypernyms and hyponyms matching. CheckAbbreviation – This algorithm uses domain specific Abbreviation dictionary to expand the abbreviations TokenMatcher – This algorithm uses the Porter Stemmer to find the roots of the words. It also uses tokenization based on punctuation and capitalization of letters.

30 MWSAFMETEOR-SWebServiceAnnotationFramework where,ms1 = MatchScore ( NGram ) ms2 = MatchScore ( Synonym Matching ) ms3 = MatchScore ( Abbreviation Expansion ) ms4 = MatchScore ( Token Matching ) WSDL ConceptOntological ConceptElemMatchAlgorithm windWindEvent0.639NGram windWindChill0.478NGram snowSnowFall1Synonyms slpSeaLevelPressure1Abbreviation relative_humidityRelativeHumidity1NGram Example MWSAF – Element level Match

31 MWSAFMETEOR-SWebServiceAnnotationFramework MWSAF – Schema level Match Definition The Schema level match is the measure of structural similarity between two concepts It is based on sub-concept similarity (subConceptSim) and sub-concept match (subConceptMatch).

32 MWSAFMETEOR-SWebServiceAnnotationFramework MWSAF – Schema level Match Definition : Sub-concept Similarity ( subConceptSim ) The sub-concept similarity is the average match score of each individual sub-element of the concept Definition : Sub-concept Match ( subConceptMatch ) The sub-concept match is the fraction of total number of sub- elements of a concept that are matched

33 MWSAFMETEOR-SWebServiceAnnotationFramework Example WSDL Concept Pressure Ontological Concept PressureEvent MS delta----0 slpSea Level Pressure1 relative_humidityRelativeHumidity1 subConceptSim ( Pressure, PressureEvent ) = ( 1 + 1 + 0 ) / 3 = 0.667 subConceptMatch ( Pressure, PressureEvent ) = 2 / 3 = 0.667 MWSAF – Schema level Match (example)

34 MWSAFMETEOR-SWebServiceAnnotationFramework MWSAF – Categorizing WSDL Average Service Match ( avgServiceMatch ) Calculated as the average match of all the concepts of a WSDL schema and a domain ontology The domain of the ontology corresponding to the best average service match also represents the domain of the Web service Normalized on the scale of 0 to 1 where,k = number of mapped concepts n = number of concepts in WSDL schema

35 MWSAFMETEOR-SWebServiceAnnotationFramework MWSAF – Annotating WSDL Average Concept Match ( avgConceptMatch ) Calculated as the average match of the mapped concepts of a WSDL schema Based on this measure user can decide whether to accept mappings for annotation or not It is normalized on the scale of 0 to 1

36 MWSAFMETEOR-SWebServiceAnnotationFramework Outline Introduction METEOR-S Project @ UGA SchemaGraph Architecture Matching algorithm Results Conclusions and Future Work

37 MWSAFMETEOR-SWebServiceAnnotationFramework MWSAF – Categorizing WSDL 6 different Web services are compared to 5 ontologies to get avgServiceMatch values for each of them. Service belongs to the domain of the ontology for which it gives best avgServiceMatch. E.g. AirportWeather service best matches to weather-ont ontology and hence belongs to weather domain

38 MWSAFMETEOR-SWebServiceAnnotationFramework MWSAF – Categorizing WSDL 24 Web services from Weather and Geographical domain are categorized with different threshold (CT) values. For CT = 0.4, two services are categorized wrongly For CT = 0.5, all the Web services are not categorized

39 MWSAFMETEOR-SWebServiceAnnotationFramework MWSAF – Testing With original Geo ontologies, services gave low match scores By adding few more concepts, the match scores improved for many services. Plot of number of mapped concepts strengthens this observation

40 MWSAFMETEOR-SWebServiceAnnotationFramework MWSAF – Testing Problems Match scores are low All concepts are not mapped Reasons Match algorithms can be improved Domain specific synonyms and abbreviations can improve avgConceptMatch Domain specific match algorithms can be implemented Ontologies are still in development stage and not comprehensive enough to contain all the concepts from the domain Need ontologies specifically designed for Web services WSDL files are automatically generated by web servers and hence not all IO parameters have meaningful names

41 MWSAFMETEOR-SWebServiceAnnotationFramework Outline Introduction METEOR-S Project @ UGA SchemaGraph Architecture Matching algorithm Results Conclusions and Future Work

42 MWSAFMETEOR-SWebServiceAnnotationFramework Conclusions Created an initial prototype for semi-automatic annotation of Web services Initial results promising, but a lot of improvement possible WSDL-S adds semantics to Web services with minimal changes Future Work Apply machine learning techniques to improve accuracy Build a test bed for Semantic Web Services Eclipse based tool release in 1 montg

43 MWSAFMETEOR-SWebServiceAnnotationFramework MWSAF – Screenshot 1 2 1 3 4 5

44 MWSAFMETEOR-SWebServiceAnnotationFramework References 1.D. Fensel, C. Bussler, "The Web Service Modeling Framework WSMF", Technical Report, Vrije Universiteit Amsterdam 2.METEOR-S: Semantic Web Services and Processes, http://swp.semanticweb.org http://swp.semanticweb.org 3.A. Ankolekar, M. Burstein, J. Hobbs, O. Lassila, D. Martin, D. McDermott, S. McIlraith, S. Narayanan, M. Paolucci, T. Payne, and K. Sycara, "DAML-S: Web service Description for the Semantic Web," in Proceedings of the 1st International Semantic Web Conference (ISWC 2002) 4.S. Agarwal, S. Handschuh, and S. Staab Surfing the Service Web, in Proceedings of the 2nd International Semantic Web Conference (ISWC 2003) 5.M. Klein, Combining and relating ontologies: an analysis of problems and solutions. in (IJCAI 2001) 6.E. Rahm and P. A. Bernstein. A survey of approaches to automatic schema matching. In The VLDB Journal: Volume 10 Issue, (2001), pages 334-350, 2001. 7.H. Do, S. Melnik, and E. Rahm. Comparison of schema matching evaluations. In Proceedings of the 2nd Int. Workshop on Web Databases (German Informatics Society), 2002 8.Pottinger, R. A. and P. A. Bernstein, Merging Models Based on Given Correspondences. Proc. 29th VLDB Conference


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