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Using Well-Founded Provenance Ontologies to Query Meteorological Data

LabData. Using Well-Founded Provenance Ontologies to Query Meteorological Data . Thiago Marcos da Silva Barbosa , Ednaldo O. Santos , Gustavo B. Lyra, Sérgio Manuel Serra da Cruz. Federal Rural University of Rio de Janeiro Database Lab. Why Meteorology ?. PROBLEM :

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Using Well-Founded Provenance Ontologies to Query Meteorological Data

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  1. LabData Using Well-Founded Provenance Ontologies to Query Meteorological Data Thiago Marcos da Silva Barbosa, Ednaldo O. Santos, Gustavo B. Lyra,Sérgio Manuel Serra da Cruz Federal Rural Universityof Rio de Janeiro DatabaseLab

  2. WhyMeteorology? • PROBLEM: • The investigation of extreme hydrometeorological events requires lots of data from sensors huge data bases. • It is not trivial for meteorologists to create SPARQL queries that involve meteorological data, provenance metadata and also ontology classes. • GOAL: Presentan approach that uses well-foundedontologiesandprovenance management techniques to aidresearchers to investigatethe cause oferroneousvaluesdetectedatanypointofthepre-processingchainofmeteorological data. • Letthemeteorologists to createsimplequeriesevenwithoutknowingthesyntaxofthe SPARQL language.

  3. How? • Using: • Ontologicallywell-founded UML modelingprofile (OntoUML). A profile to developwell-foundedontologiesthatreflectsthestructureandaxiomatizationofUnifiedFoundationOntology (UFO) (Guizzard, 2005). • Open proVenanceOntology (OvO) (Cruz, 2012) to modelMeteoro ontology. • Developing: • A web-basedtoolthatallowstheresearches to navigatethroughtheconceptsandproperties, andgraphicallydevelopsimplequeriesbyselectingfeatureslikeontologyclass, object, propertiesandvalues to besearched.

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