Life Sciences Linked Open Data Cloud Ali Hasnain et al Insight Center for Data Analytics National University of Ireland Galway Agenda Motivation Linked Life Sciences Roadmap Cataloguing and Linking ID: 803395
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Slide1
A Provenance assisted Roadmap for
Life Sciences
Linked Open Data Cloud
Ali
Hasnain et. al
Insight
Center for Data
Analytics
National University of Ireland,
Galway
Slide2AgendaMotivationLinked Life Sciences RoadmapCataloguing and LinkingExtending Catalogue – Metadata & ProvenanceQuery Engine
Results
Slide3MotivationBiomedical Data is heterogeneous and spread across multiple sources (SPARQL endpoints).Navigation is a challenge.C
ontaining trillions of triples and represented with insufficient vocabulary reuse.Biologists sometimes want to get more information regarding the data including its source
, creator, publisher and also statistics with respect to its size (Metadata & Provenance).3
Slide4How to deal heterogeneous data?
DrugBank
DailyMed
CheBI
, KEGG
Reactome
Sider
BioPax
Medicare
Slide5We want to query the content, not the source
Proteins
Molecules
Genes
Diseases
Slide6A Linked Life Sciences Roadmap
Proteins
Molecules
Genes
Diseases
:
Protein
:
Molecule
:
Gene
:
Disease
Uniprot
PDB
Pfam
PROSITE
ProDom
Uniref
UniPark
Daily
med
Drug
Bank
ChemBL
Pub
Chem
KEGG
Gene
Ontology
GeneID
Affy
metrix
Homo
gene
MGI
Disea
some
SIDER
Slide72- Possible SolutionsTo assemble queries over multiple graphs at multiple endpoints, either: vocabularies and ontologies are reused, Or translation maps between different terminologies are created (“a posteriori integration
”)
Slide8a-priori
v.s a-posteriori Integration
8
Slide9Cataloguing and Linking9
Slide10Describing DataSets- an Extract from Catalogue
Slide11Extending Catalogue – Metadata & Provenance
Slide12Slide13Slide14Query Enginehttp://srvgal86.deri.ie:8000/graph/Granatum
Slide15Visual & Graphical View
Slide16SPARQL Endpoints returning results per query
Slide17Runtimes taken by different queries (Max, Min, Average, Median)
Slide18