Date: 23/09/2010FIS 2010 DoctoralConsortiumEnabling Semantic Integration of Streaming Data SourcesJean-Paul CalbimonteOntology Engineering Group. Departamento de Inteligencia Artificial.Facultad de Informática, Universidad Politécnica de Madrid. Campus de Montegancedo s/n. 28660 Boadilla del Monte. Madrid. Spain{jpcalbimonte}@fi.upm.esSupervisor: Oscar CorchoDC Scientific advisor: AchimRettinger
IndexIntroductionProblem statementMain research questionsApproachProposed solutionWork done so farEvaluation	Future work2EnablingSemanticIntegration of Streaming Data Sources
Introduction & Scope3Streaming Data
 Continuously appended data
 Potentially infinite
 Time-stamped tuples
 Continuous queries
 Latest used in queries
 Windows: time information  and tuple based(t9, a1, a2, ... , an)(t8, a1, a2, ... , an)(t7, a1, a2, ... , an)......(t1, a1, a2, ... , an)......Window [t7 - t9]Streaming Data Sensor Networks characteristics
 Cheap, Noisy, Unreliable (depends)
 Low computational, power resources, storage
 Distributed query execution
 Routing, OptimizationQueryEnablingSemanticIntegration of Streaming Data Sources
Problem StatementHeterogeneous sources: schemas, stream rates, QoS, delivery mechanisms
Distributed sources
Semantic heterogeneity
Semantic data provision only for stored data
Need for live streaming continuous queriesSensor NetworkDatabase DataIntegrateDecl. QueryIntegrated viewStream Data4SemanticIntegrationStreaming Data Sources
Main Research QuestionsProvide semantic query interfaces for streaming data

Enabling semantic integration