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Semantic extensions to ecoRelevé. Olivier Rovellotti. The projet The Sem Web The extentions. Reduce Software complexity. F or who ?. People we know:. People we don’t know?. What for?. Analyze data. Ask Questions. Define Protocols. Collect data. Data Admin. Research.
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Semantic extensions to ecoRelevé • Olivier Rovellotti
The projet • The Sem Web • The extentions
Reduce Software complexity
For who? People we know: People wedon’tknow?
What for? Analyze data Ask Questions Define Protocols Collect data Data Admin
Research DBA/GIS Professional Citizen Science PHD 3 Modules
2012 Life Science
What is it good for? • Better annotations • Easier data integration • More extensible • More expressive
Aggregate data Controlled Vocabularies: Build protocols forms Enhance existing dataset
ecoRelevé Core
1.0 Data integration Observation Layers
Data enhancement ecoRelevé explorer
4 dimensions Space Biology People Time
GeoSparql Localities Protected Areas Conservation Status Work Space Time FOAF Biology People Family Friends At the same time as Last week
Milan royal Milvusmilvus RedKite
SPARQL: Catch the frog TAISTY! ecoReleve select ?scientificName, ?status, ?lat, ?long FROM <urn:rdf.TdwgFroggyChallenge> where { ?s rdf:typeuniprot:Molecule . ?s terms:relation ?id. ?s terms:subject ?taxonInGB . ?id geo:lat ?lat. ?id geo:long ?long. ?taxonInDbPediadbOwl:conservationStatus ?status. ?taxonInGBrdfs:seeAlso ?taxonInDbPedia. ?taxonInGBuniprot:scientificName ?scientificName. } SparQL
Take home message: • There is a learningcurve • But RDF is not thatdifficult • One API isbetterthan 10 • Weneed data in RDF to experiment • Reasoningis for later…
Thanks .. @orovellotti