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How? Using: – Ontologically well-founded UML modeling profile (OntoUML). A profile to develop well-founded ontologies that reflects the structure and axiomatization of Unified Foundation Ontology (UFO) (Guizzard, 2005). – Open proVenance Ontology (OvO) (Cruz, 2012) to model Meteoro ontology. Developing: – A web-based tool that allows the researches to navigate through the concepts and properties, and graphically develop simple queries by selecting features like ontology class, object, properties and values to be searched.
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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
LabData
Federal Rural University of Rio de JaneiroDatabase Lab
Why Meteorology?• 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: Present an approach that uses well-founded ontologies and provenance management techniques to aid researchers to investigate the cause of erroneous values detected at any point of the pre-processing chain of meteorological data. – Let the meteorologists to create simple queries even without knowing the syntax
of the SPARQL language.
How?• Using:
– Ontologically well-founded UML modeling profile (OntoUML). A profile to develop well-founded ontologies that reflects the structure and axiomatization of Unified Foundation Ontology (UFO) (Guizzard, 2005).
– Open proVenance Ontology (OvO) (Cruz, 2012) to model Meteoro ontology.
• Developing:– A web-based tool that allows the researches to navigate through the
concepts and properties, and graphically develop simple queries by selecting features like ontology class, object, properties and values to be searched.
