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Exploiting provenance to make sense of automated decisions in scientific workflows ,[object Object],[object Object],[object Object],[object Object]
Outline ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Scope of provenance analysis ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Motivation ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Example: protein identification process Data output Protein identification algorithm “ Wet lab” experiment Protein Hitlist Protein function prediction Correct entry    true positive This evidence is independent of the algorithm / SW package It is  readily available and inexpensive  to obtain Evidence : mass coverage (MC)  measures the amount of protein sequence matched Hit ratio (HR)  gives an indication of the signal to noise ratio in a mass spectrum ELDP  reflects the completeness of the digestion that precedes the peptide mass fingerprinting
Quality process components ,[object Object],[object Object],[object Object],PMF score =  (HR x 100) +  MC +  (ELDP x 10)‏ Quality assertion : ,[object Object],[object Object],[object Object],[object Object],actions rules: if (score < x)‏ then reject Collect evidence  Evaluate conditions Execute actions Compute assertions Protein identification Protein Hitlist Protein function prediction Quality filtering
From quality processes to quality workflows ,[object Object],[object Object],[object Object],[object Object]
Example: original proteomics workflow Quality flow embedding point
Example: embedded quality workflow
Qurator provenance component ,[object Object],scope: workflow run data being quality assessed quality metrics applied to the data value of metric on the data evidence used to compute metrics quality rules based on metrics values statistics
Semantics of quality processors upper ontology for Information Quality extensions to the proteomics domain services and data
Provenance model ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Static model (fragment)‏
Dynamic model (fragment)‏ return all action outcomes for a given workflow and data item: SELECT  ?action ?outcome ?workflow  WHERE { ?binding data_item ”P33897” .  ?binding action name ?action .  ?binding value ?outcome .  ?binding workflow ?workflow .  ?binding rdf:type ”actionBinding” .  FILTER (regex(?workflow, ”4IPQF26RXW2”)) }
Provenance service interface ,[object Object],[object Object],[object Object],[object Object]
Conclusions ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

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Paper presentation @IPAW'08

  • 1.
  • 2.
  • 3.
  • 4.
  • 5. Example: protein identification process Data output Protein identification algorithm “ Wet lab” experiment Protein Hitlist Protein function prediction Correct entry  true positive This evidence is independent of the algorithm / SW package It is readily available and inexpensive to obtain Evidence : mass coverage (MC) measures the amount of protein sequence matched Hit ratio (HR) gives an indication of the signal to noise ratio in a mass spectrum ELDP reflects the completeness of the digestion that precedes the peptide mass fingerprinting
  • 6.
  • 7.
  • 8. Example: original proteomics workflow Quality flow embedding point
  • 10.
  • 11. Semantics of quality processors upper ontology for Information Quality extensions to the proteomics domain services and data
  • 12.
  • 14. Dynamic model (fragment)‏ return all action outcomes for a given workflow and data item: SELECT ?action ?outcome ?workflow WHERE { ?binding data_item ”P33897” . ?binding action name ?action . ?binding value ?outcome . ?binding workflow ?workflow . ?binding rdf:type ”actionBinding” . FILTER (regex(?workflow, ”4IPQF26RXW2”)) }
  • 15.
  • 16.

Hinweis der Redaktion

  1. Searching for “nuggets of quality knowledge”
  2. Embedding the sub-flow requires a deployment descriptor : Adapters between host flow and quality subflow Data and control links between host flow tasks and quality flow tasks