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SCRY @ ISWC'15, Diversity++

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Presenting the SPARQL Compatible seRvice laYer (SCRY) at the Diversity++ workshop of the International Semantic Web Conference 2015. See also the paper published in its proceedings.

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SCRY @ ISWC'15, Diversity++

  1. 1. SCRY SPARQL Compatible Service Layer Diversity++ Workshop @ ISWC 2015 Bas Stringer, VU Amsterdam b.stringer@vu.nl
  2. 2. 37B triples > 600K RDF dumps > 640 SPARQL endpoints Source: http://lod-cloud.net/
  3. 3. Different Users → Different Needs ● Domain-specific... – Data – Applications – Problems (Challenges!) – Solutions ● No “One Size Fits All” fix! But why not?
  4. 4. Data != Knowledge ● Semantic Web → data ● Answers ← knowledge ● Typically can't be precomputed – Must be done at query time! ● Make “implicit knowledge” explicit – Qualitative reasoning: OWL – Quantitative reasoning: Depends! ? Reasoning
  5. 5. Quantitative Reasoning ● “I have people's heights and weights. BMI?” ● “I have people's BMIs. Standard deviation?” ● “Is there a correlation between geospatial location and BMI?” ● “Find genes with mutations which frequently co- occur with obesity. Are there drugs which target these genes?” Do other traits correlate? What about similar genes?
  6. 6. Quantitative Reasoning ● Current approaches: – Built-in SPARQL functions – Pre- and/or post-scripting – Extensible Value Testing – Linked Data APIs – Endpoint customization
  7. 7. SCRY ● SPARQL compatible service layer – Lightweight, federation-oriented endpoint – Graph patterns encode service calls – Input/output = RDF – Graph generated on demand
  8. 8. Easy to Customize! ● SCRY is written in Python – Implement services in Python – … or call them from commandline – … or as a webservice! From paper “To SCRY Linked Data: Extending SPARQL the Easy Way”
  9. 9. Example 1: Standard Deviation Demo data:
  10. 10. Bind a comma-separated list of the ages and lengths Federate a query to SCRY Every unique combination of inputs and outputs get their own separate subgraph You can call the same service with different inputs, and different services with the same inputs! Use the output back at the primary endpoint / query Which authors have an age and length within one SD of the mean?
  11. 11. Example 2: BLAST Protein Structure Function Disease ExpressionHomolog
  12. 12. Which tissues express Hemoglobin β? How many homologs are coexpressed there? ● Get protein identifier ● Get homologs ● Get expression data ● Count! { }
  13. 13. Pros Cons ● Flexible – Easily customized ● Reusable – Share services ● Local – Private data – Private resources ● Interoperable – Query federation ● Query federation – No direct data access – Network latency – Authorization
  14. 14. Outlook ● Develop a user community – Community-managed service repository ● Security and authorization features – Enable public SCRY orbs ● Solve current problems in bioinformatics – E.g. queries involving homology! ● Find use cases in other fields of science! – (Co-)develop required & desired services – Get in touch with interested collaborators
  15. 15. Thank you for your time! To SCRY Linked Data: Extending SPARQL the Easy Way Diversity++ Workshop @ ISWC 2015

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