KUPKB: Sharing, Connecting and Exposing Kidney and UrinaryKnowledge using RDF and OWL              www.kupkb.org        Ju...
The problem domainThousands of studies have been conducted by the kidney research community          On different species...
Where does the data go?      Bespoke kidney laboratory databases                                             Research Pape...
The Kidney and Urinary Pathway Knowledge Base:                                        SHARE AND CONNECTThe iKUP Browser:  ...
Stucture Populous                           Experimental dataKUP Ontology  (schema)                                  Right...
Ontologies provide the schema                  What has been observed, where and when?      Mouse anatomy                 ...
Ontologies by stealth                 The domain experts are the experts so get them build it                             ...
Describing/Collecting experimental dataGathering good meta-data AND data again by stealth using RightField                ...
Describing/Collecting experimental dataGathering good meta-data AND data again by stealth using RightField                ...
Mashing it all together Kidney and Urinary Pathway Ontology                          Experimental data~1800 classes (~40,0...
SPARQLing resultsMake it all RDF/OWL and expose a SPARQL endpoint…                                       …then we are done...
The iKUP browserBuilt as an easy-to-use and light Google Web Toolkit application
To expose data from the KUPKB
Doing some biology1. A biological question         2. No answer with classical toolsCan calreticulin be associated   Searc...
Reusing and BuildingOntologies provide the schema                        Experimental data                                ...
Reusing and Building    Ontologies provide the schema                          Experimental dataKidney and Urinary Pathway...
What next User study and evaluation experiments ongoing with  Manchester Web Ergonomics Lab Application to other biologi...
Acknowledgments•   Simon Jupp•   Stuart Owen, Matthew Horridge, Katy Wolstencroft and Carole Goble @    University of Manc...
Thank you for listening…www.kupk b .or
Some rough stats…• 195 KUP experiments integrated• KUPKB RDF store ~35M triples• KUPK Ontology ~1800 classes. ~40,000 afte...
Summary   The KUPKB RDF store is a mashup of biological knowledge relating to the    KUP domain   Ontologies provide the...
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J Klein - KUPKB: sharing, connecting and exposing kidney and urinary knowledge using RDF and OWL

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Presentation at BOSC2012 by J Klein - KUPKB: sharing, connecting and exposing kidney and urinary knowledge using RDF and OWL

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  • Renal physiology Human urinary protein map Renal pathophysiology Biomarker discovery
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  • J Klein - KUPKB: sharing, connecting and exposing kidney and urinary knowledge using RDF and OWL

    1. 1. KUPKB: Sharing, Connecting and Exposing Kidney and UrinaryKnowledge using RDF and OWL www.kupkb.org Julie Klein & Simon Jupp Bio-health informatics group University of Manchester
    2. 2. The problem domainThousands of studies have been conducted by the kidney research community  On different species human mouse  On different materials urine tissue cell • On different biological levels gene protein Large diversity  Integration of the knowldege is complex
    3. 3. Where does the data go? Bespoke kidney laboratory databases Research Papers Generalist databasesScattered, hidden in figures, coming in different formats Most of the data is lost!
    4. 4. The Kidney and Urinary Pathway Knowledge Base: SHARE AND CONNECTThe iKUP Browser: EXPOSE www.kupkb.org
    5. 5. Stucture Populous Experimental dataKUP Ontology (schema) RightField RDF triple store iKUP Browser KUP Knowledge Base
    6. 6. Ontologies provide the schema What has been observed, where and when? Mouse anatomy Experimental factors ontology Gene Ontology Animal model Cell type ontology Disease ontology We needed to connect these reference ontologies.Creation of a specialized Kidney and Urinary Pathway Ontology (KUPO) http://www.e-lico.org/public/kupo/
    7. 7. Ontologies by stealth The domain experts are the experts so get them build it Biological Cells Anatomy processes( (CTO) (MAO) GO)Spreadsheet OPPL Scripts Ontology Populous generates simple Excel based templates http://www.e-lico.eu/populous.html
    8. 8. Describing/Collecting experimental dataGathering good meta-data AND data again by stealth using RightField Content of the meta-data cells is constraint to the relevant set of KUPO terms http://www.sysmo-db.org/rightfield
    9. 9. Describing/Collecting experimental dataGathering good meta-data AND data again by stealth using RightField Content of the meta-data cells is constraint to the relevant set of KUPO terms
    10. 10. Mashing it all together Kidney and Urinary Pathway Ontology Experimental data~1800 classes (~40,000 after imports closure) 220 KUP experiments integrated Owl reasoning RDF triple store ~35M triples KUP Knowledge Base
    11. 11. SPARQLing resultsMake it all RDF/OWL and expose a SPARQL endpoint… …then we are done right? We can now ask queries that span several databases We can exploit OWL semantics for intelligent answers BUT! Easy to use application… …this is what the biologist really want
    12. 12. The iKUP browserBuilt as an easy-to-use and light Google Web Toolkit application
    13. 13. To expose data from the KUPKB
    14. 14. Doing some biology1. A biological question 2. No answer with classical toolsCan calreticulin be associated Search in Pubmed and Google doesto the development of human not return any relevant result!kidney disease?3. Querying the KUPKB4. Validation in the wet-lab 5. Publish an innovative resultKUPKB in silico result Accepted for publication in the FASEB J!confirmed.
    15. 15. Reusing and BuildingOntologies provide the schema Experimental data Owl reasoning RDF triple store KUP Knowledge Base
    16. 16. Reusing and Building Ontologies provide the schema Experimental dataKidney and Urinary Pathway Ontology Annotations, homogenization Tool to facilitate building of onto. Tool to facilitate data annotation Owl reasoning RDF triple store iKUP Browser KUP Knowledge Base
    17. 17. What next User study and evaluation experiments ongoing with Manchester Web Ergonomics Lab Application to other biological domains  Change the domain model in the ontologies and we can construct any organ knowledge base in this way  Already interests in gut, liver, heart and metabolic diseases
    18. 18. Acknowledgments• Simon Jupp• Stuart Owen, Matthew Horridge, Katy Wolstencroft and Carole Goble @ University of Manchester for RightField• Joost Schanstra, Panagiotis Moulos, Jean-Loup Bascands @ Renal Fibrosis Lab, Toulouse, France• Aristidis Charonis, Bénédicte Buffin-Meyer, Myriem Fernandez for the CALR example• e-LICO FP7 project and EuroKUP• Robert Stevens, ontology development, University of Manchester Open Source License: GNU Lesser General Public License Code: http://code.google.com/p/kupkb-dev/
    19. 19. Thank you for listening…www.kupk b .or
    20. 20. Some rough stats…• 195 KUP experiments integrated• KUPKB RDF store ~35M triples• KUPK Ontology ~1800 classes. ~40,000 after imports closureArchitecture• Sesame and BigOWLIM for the RDF store• Web site developed with Google web toolkit• OWL API and HermiT reasoner for classification and faceted browsing
    21. 21. Summary The KUPKB RDF store is a mashup of biological knowledge relating to the KUP domain Ontologies provide the schema and a consistent data annotation mechanism We expose this knowledge base through a simple web interface that real biologists can use, the iKUP iKUP and KUPKB provides a faster mechanism for the biologist to survey the data in biological publications and helps the hypothesis generation process. It is a testament to the tools and APIs that such applications are now being delivered at relatively low cost

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