
bbe30a9ef5ea27fafe32c152c035df26.ppt
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Context Mediation in the Semantic Web: Web Handling OWL Ontology and Data Disparity through Context Interchange Philip Tan Singapore-MIT Alliance (SMA) Stuart Madnick (Presenter) MIT Sloan School of Management smadnick@mit. edu Kian-Lee Tan Department of Computer Science, National University of Singapore 1 SMA Computer Science (CS) – Technical Program 19 -20 January 2005
Context Mediation Research and Semantic Web Research Focus on resolving semantic Conflicts amongst Heterogeneous data sources Context Mediation Research Help resolve semantic heterogeneity in OWL/RDF/XML data Focus on making the web semantically richer Semantic Web Research Provide a standard (OWL 2 etc) for representing Ontology-related knowledge
Some History p COntext INterchange (COIN) system for semantic interoperability among heterogeneous data sources (started around 1995) n p Uses COINL, based on FOL/Prolog, to model semantic knowledge (application ontology and context modifiers) Web Ontology Language (OWL) becomes W 3 C Recommendation for ontology publishing (2004) 3
Example of Context Mediation situation Note: Net. Income (profit) exceeds Total. Sales – Impressive ! (Issues: currency? Scale factor? ) 4
“Unit-of-measure mixup tied to loss of $125 Million Mars Orbiter” “NASA’s Mars Climate Orbiter was lost because engineers did not make a simple conversion from English units to metric, an embarrassing lapse that sent the $125 million craft off course. . . . The navigators ( JPL ) assumed metric units of force per second, or newtons. In fact, the numbers were in pounds of force per second as supplied by Lockheed Martin ( the contractor ). ” Source: Kathy Sawyer, Boston Globe, October 1, 1999, page 1. 5
The Context Interchange Approach Concept: Length Meters F-logic: based on FOL, uses Prolog f() meters feet Feet Shared Ontologies Source Context Conversion Libraries Context Mediator Receiver Context part length Context Transformation 17 Source Context Management Administrator Select partlength From catalog Where partno=“ 12 AY” 55. 25 Receiver 6
Web Ontology Language (OWL) p W 3 C Recommendation status n n p publish and share ontologies supporting advanced Web search software agents knowledge management Three sublanguages n n Categorization for computational guarantees OWL Lite, OWL DL, OWL Full 7
OWL in Action p Graduate. Students are Students with a degree of either BA or BS Class <owl: Class rdf: ID="Student“/> <owl: Class rdf: ID="Graduate. Student"> <rdfs: sub. Class. Of> Restriction definition <owl: Restriction> <owl: on. Property> <owl: Object. Property rdf: about="#has. Degree"/> </owl: on. Property> Inheritance </owl: Restriction> </rdfs: sub. Class. Of> <rdfs: sub. Class. Of rdf: resource="#Student"/> </owl: Class> 8
OWL in Action p Graduate. Students are Students with a degree of either BA or BS <owl: Class rdf: ID="Student“/> <owl: Class rdf: ID="Graduate. Student"> <rdfs: sub. Class. Of> <owl: Restriction> <owl: on. Property> <owl: Object. Property rdf: about="#has. Degree"/> </owl: on. Property> <owl: some. Values. From> <owl: Class> <owl: one. Of rdf: parse. Type="Collection"> <Degree rdf: ID="BA"/> Or is it “AB” and “SB”? <Degree rdf: ID="BS"/> Some Harvard degree abbreviations appear </owl: one. Of> to be backwards because they follow the tradition of Latin degree names. The </owl: Class> undergraduate degrees awarded by Harvard </owl: some. Values. From> University are the A. B. and S. B. The A. B. is </owl: Restriction> </rdfs: sub. Class. Of> <rdfs: sub. Class. Of rdf: resource="#Student"/> </owl: Class> an abbreviation for the Latin name for the bachelor of arts (B. A. ) degree "artium baccalaureus. " The S. B. , Latin for "scientiae 9 baccalaureus, " is the bachelor of science (B. S. ).
Why not be explicit about context ? (i. e. , include in data – DB or XML) - Hard to anticipate need (why include currency, if everything is US dollars) - Hard to get everyone to agree to same context Picture of old lady or young lady ? 10
Data source. . . (how do you cite in a Journal article? ) 11
Context Interchange in OWL (COIN-OWL) Extend COIN p Two sides of COIN p n n p OWL as COIN’s application ontology representation benefits COIN as ‘meta-ontology’ for OWL ontology interoperability benefits OWL Rule Markup (Rule. ML) Language n n n basis for an integrated rule-markup approach specification for immediate rule interchange Hierarchical language subclasses p p p Datalog Hornlog For brevity, COIN-OWL 12
Design Approach to Use OWL to Represent COIN Ontology p p Preserve constraint programming engine in the e. COIN prototype Layered architecture: 1. 2. 3. p Domain ontology modeled in OWL ontology transformed to e. COIN Prolog Transformed ontology fetched to e. COIN engine Minimal impact to existing implementation 13
3 -Tier Approach ECOIN Context Mediation System (3) ECOIN - (2) Prolog Program COINOWL Ontology (1) Ontology Administrator Context Mediation and Query Processing (unchanged) Automated Ontology Conversion Ontology Development & Editing 14
Ontology Model Design p Domain Model n p Source Sets n p Physical relations and data source Context Axioms n p Semantic types, modifiers, attributes Context, modifier values, conversion functions Elevation Axioms n n Semantic relations – mapping source sets to domain model Context relations – mapping source sets to contexts 15
Domain and Context Model in COIN-OWL <coin: Modifier rdf: ID="mod_scale. Factor"> <coin: Modifier. Name rdf: datatype="&xsd; string">scale. Factor</coin: Modifier. Name> <coin: Modifier. To rdf: resource="#basic"/> <coin: Modifier. From rdf: resource="#company. Financials"/> </coin: Modifier> <coin: Modifier rdf: ID="mod_currency"> <coin: Modifier. Name rdf: datatype="&xsd; string">currency</coin: Modifier. Name> <coin: Modifier. To rdf: resource="#currency. Type"/> <coin: Modifier. From rdf: resource="#company. Financials"/> </coin: Modifier> <coin: Semantic. Type rdf: ID="company. Financials"> <coin: Modifiers rdf: resource=”#mod_scale. Factor”></coin: Modifiers> <coin: Modifiers rdf: resource=”#mod_currency”></coin: Modifiers> </coin: Semantic. Type> 16
Challenging area to using Semantic Web: Modeling Conversion Functions p Previous (RDF/XML) work <coin: Ont_Modifier. Conversion. Function> convfunc|rule(cvt(company. Financials, O, currency, Ctxt, Mvs, Vs, Mvt, Vt), (attr(O, fy. Ending, Fy. Date), value(Fy. Date, Ctxt, Date. Value), olsen_p(Fc, Tc, Rate, Txn. Date), value(Fc, Ctxt, Mvs), value(Tc, Ctxt, Mvt), value(Txn. Date, Ctxt, Date. Value), value(Rate, Ctxt, Rv), Vt is Vs * Rv)). rule(month("Oct", 10), (true)). rule(month("Dec", 12), true)). |company. Financials|currency </coin: Ont_Modifier. Conversion. Function> 17
…Conversion Functions Using Rule. ML p Month name lookup: rule(month("Jan", 01), (true)). p <fact> <_head> <atom> <cterm> <_opc><ctor>rule</ctor></_opc> <cterm> <_opc><ctor>month</ctor></_opc> <ind>Jan</ind> <ind>01</ind> </cterm> <ind>true</ind> </cterm> </atom> </_head> </fact> 18
Master Plan of COIN Representation in OWL 19
COIN-OWL Development Platform OWL Editor n n p Protégé –extensible architecture, de facto p. OWL – web-based development environment Why Protégé? n n n Easy to use Actively supported Plugins for visualization, diagram p Plugin for Protégé p Input: COIN-OWL ontology in OWL, Rule. ML n Output: e. COIN Prolog application ontology Developed in Java 1. 4, Protégé OWL API, XSLT n 20
COIN-OWL Ontology 21
Rule. ML Conversion Functions 22
Generated e. COIN Prolog View 23
Conclusion p OWL ontology model for COIN framework n n OWL Lite Rule. ML COIN-OWL prototype as reference implementation p Adoption of W 3 C standard reaches wider spectrum of audience p Opportunity to enhance Semantic Web p 24
Future Work p Investigate Rule. ML Lite, Semantic Web Rule Language (SWRL) n n p Address OWL ontology interoperability n n p Tighter cohesiveness Reference to OWL ontology via rdf: resource Problem similar to heterogeneous data integration Use COIN for context mediation among ontologies On-going extensions to COIN research n Addressing temporal and aggregational context 25
The 1805 Overture In 1805, the Austrian and Russian Emperors agreed to join forces against Napoleon. The Russians said their forces would be in the field in Bavaria by Oct. 20. The Austrian staff planned based on that date in the Gregorian calendar. Russia, however, used the ancient Julian calendar, which lagged 10 days behind. The difference allowed Napoleon to surround Austrian General Mack's army at Ulm on Oct. 21, well before the Russian forces arrived. 26
bbe30a9ef5ea27fafe32c152c035df26.ppt