practical interoperability across semantic stores of data for blah blah blah

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Practical interoperability across semantic stores of data for blah blah blah eol.org @eol @cydpar r

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Practical interoperability across semantic stores of data for blah blah blah. eol.org @ eol @ cydparr. The road to TraitBank. In second year of 2 year project: Marine Expert Audience Conservation science Virtuoso triple store - PowerPoint PPT Presentation

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Page 1: Practical  interoperability across  semantic stores of data  for blah blah blah

Practical interoperabilityacross semantic stores of data for blah blah blah

eol.org@eol@cydparr

Page 2: Practical  interoperability across  semantic stores of data  for blah blah blah

The road to TraitBank In second year of 2 year project: Marine

Expert AudienceConservation science

Virtuoso triple store<EOL taxon id> <hasAvgBodyMass in g> <value><EOL taxon id> <preysOn> <scientific name>

Beta testing NOW for public launch early 201421 datasets with 2.8 million data records for 520,000 taxa

Harvest, display, curate, search, download

MOST DATA NOT BORN SEMANTIC

From text miningFrom literature tablesFrom data papersFrom databases

Page 3: Practical  interoperability across  semantic stores of data  for blah blah blah

Term URIs from existing ontologies

• Statistics from Semantic Science Integrated Ontology• Units Ontology• Environments Ontology EnvO• Gene Ontology• ETHAN (Natural history, with Joel Sachs)• Vertebrate Trait Ontology• Plant Trait Ontology

• Where necessary: request terms• Last resort: create provisional terms with

http://eol.org/schema/terms/xxxx• Of course, also using unique EOL taxon identifiers, which we’ve

mapped to identifiers of other projects

e.g. those registered in bioportal.bioontologies.org

Page 4: Practical  interoperability across  semantic stores of data  for blah blah blah

Known URIs tool

Only light reasoning so far– just to infer inverse relationships like “eats” and “is eaten by”

Page 5: Practical  interoperability across  semantic stores of data  for blah blah blah

14 datasets with 25k taxa, 422k interactions, for 3k locationsalpha version of ingestion, normalization, aggregationalpha version of web APIalpha version of data exports

GLoBI http://globalbioticinteractions.wordpress.com/Jorrit Poelen, Chris Mungall, James Simon GoMexSi

Page 6: Practical  interoperability across  semantic stores of data  for blah blah blah

GLoBI ontology workhttps://github.com/jhpoelen/eol-globi-data/tree/master/e

ol-globi-ontology

Interaction processes from Gene OntologyRelations from OBO Relations OntologyLife cycle stages and body parts from UBERONObservation and specimen terms from variousBehaviors from NeuroBehaviorOntology and Habitat keywords from Environment Ontology

New terms:/eats, /interactsWith, /preysUpon, /hasHost, /hosts, /parasitizes

Page 7: Practical  interoperability across  semantic stores of data  for blah blah blah

Adding data

Page 8: Practical  interoperability across  semantic stores of data  for blah blah blah

To do

• Term evaluation and recommendations• Map similar terms• Map terms to upper ontology like Species

Profile Model• Leverage reasoning for data validation

To access to the Beta test, happening NOWSend your EOL login to:

@cydparr [email protected]