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Capturing the context: one small(ish step for modellers, one giant leap for mankind.

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Written and presented by Mihai Glont (EMBL-EBI, UK), at the Reproducible and Citable Data and Model Workshop, September 14th -16th 2015.

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Capturing the context: one small(ish step for modellers, one giant leap for mankind.

  1. 1. One small(ish) step for modellers, one giant leap for mankind Capturing the context Mihai Glonț Reproducible and Citable Data and Models Warnemuende September 2015
  2. 2. A simple(?) question  How easy is it to find reusable models?  Reusable should entail, at least – Reproducible – Friendly licence – Understandable
  3. 3. Is this understandable?
  4. 4. Problems  How do we recognise concepts? Is adenosine5PrimePhospate a better variable name than a? Do all modellers know the same amount information about ATP?  How can we uniquely identify the concepts involved in a modelling exercise?
  5. 5. A brief (and biased) history of the Web Web 1.0 - basic HTML pages (personal web sites on Geosites)
  6. 6. Web 2.0 ● Prevalence of content generators ● Social media ● Rich user interfaces ● Folksonomies ● Software as a service
  7. 7. Web 3.0 ● Semantic Web ● “The Semantic Web provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries" (W3C) ● Machines understand the data on the web and can reason about it ● Implicit knowledge is captured in a machine-processable manner ● What holiday options are there for a family of four for 10 days, somewhere sunny and close to the sea, with good food and a budget of EUR 3000?
  8. 8. Semantic web overview ● Taxonomies and ontologies define concepts (resources) and ontologies ● Identification through URIs ● Data is exchanged as RDF
  9. 9. Ontologies ● Define concepts, instances, attributes and relationships ● Workshop is a kind of Thing ● Workshop hasA location
  10. 10. Linking ontologies
  11. 11. RDF Primer ● Resource Description Framework ● Documents consist of a series of statements ● Statements (triples) follow the following syntax ● Subject - Predicate – Object
  12. 12. A selection of ontologies for life scientists ● ChEBI: ● GO: ● BRENDA Tissue Ontology: ● FMA: ● Human disease ontology: ● TEDDY: ● KiSAO: ● SBO:
  13. 13. Identifiers, identifiers, identifiers ● Is the same as wwtax.cgi?mode=Info&id=9606 or ● What if the URIs change? ● What if the URIs don't point to anything?
  14. 14. Introducing ● The aim of the project is to provide unique, stable, resolvable and location-independent URIs to identify and to locate scientific data ● Community-driven ● Free to use
  15. 15. Registry 500+ curated data collections 500+ curated data collections
  16. 16. Creating unique URIs • Homo sapiens in Taxonomy (9606) [Data collection] [Entity identifier]
  17. 17. Creating resolvable URIs 9606 9606 • URI to identify the entity 'Homo sapiens' in the data collection Taxonomy http://www.ncbi.nlm.nih.go v/Taxonomy/Browser/wwwtax. cgi?mode=Info&id=9606 omy/9606 a/view/Taxon:9606 ResourceResource ResourceResource ReferenceReference Primary 9606 9606
  18. 18. Inter-conversion of identifier schemes • Registry records different identifier schemes • Web service for inter-conversion between identifier schemes 6 6 6 6
  19. 19. Support for different formats TaxonomyTaxonomy htmlhtml htmlhtml RDFRDF jsonjson • The Registry records the formats provided by the various data resources
  20. 20. BioModels
  21. 21. Model workflow within BioModels
  22. 22. BioModels model display
  23. 23. BioModels model display
  24. 24. BioModels model display
  25. 25. BioModels model classification
  26. 26. Quo vadis? ● Model curation is hard ● Model annotation is laborious ● We moved from lack of methods to scalability and usability issues ● Towards semi-automated annotation based on model clustering ● User-friendly tools for annotating models