Provenance Management Framework Satya S. Sahoo Kno.e.sis Center, Wright State University In Collaboration with Tarleton Lab, University of Georgia and Microsoft Research 2

Outline Provenance – Introduction Provenance Representation Classification of Provenance Queries & Query Operators Provenance Query Engine T.cruzi SPSE Provenance Management System 3

Provenance – Introduction *T.cruzi Semantic Problem Solving Environment Project, Courtesy of D.B. Weatherly and Flora Logan, Tarleton Lab, University of GeorgiaT.cruzi Semantic Problem Solving Environment Project Sequence Extraction Plasmid Construction Transfection Drug Selection Cell Cloning Gene Name 3‘ & 5’ Region Knockout Construct Plasmid Drug Resistant Plasmid Transfected Sample Selected Sample Cloned Sample T.Cruzi sample Cloned Sample Gene Name ? Gene Knockout and Strain Creation * Provenance from the French word “provenir” describes the lineage or history of a data entity For Verification and Validation of Data Integrity, Process Quality, and Trust Application of Provenance Metadata beyond verification and validation – eScience Data Management 4

Outline Provenance – Introduction Provenance Representation Classification of Provenance Queries & Query Operators Provenance Query Engine T.cruzi SPSE Provenance Management System 5

Provenir ontology PROCESS AGENT DATA has_agent participates_in contained_in Transfection Machine Sequence Extraction Plasmid Construction Transfection Drug Selection Cell Cloning Gene Name 3‘ & 5’ Region Knockout Construct Plasmid Drug Resistant Plasmid Transfected Sample Selected Sample Cloned Sample T.Cruzi sample A Common Provenance Model defined in OWL-DL – Provenir ontology Provenance Metadata as RDF – allows use of Semantic Web Reasoning Framework A Suite of Domain-specific Provenance ontologies - Provenir as Common Reference Model Three Base Classes – 8 specialized Sub-classes, Eleven Foundational Relations – reuse of Relation Ontology 6

Domain-specific Provenance: Parasite Experiment ontology agent process data_collection data parameter spatial_parameter domain_parameter temporal_parameter sample Time:DateTime Descritption transfection_buffercell_cloning strain_creation_ protocol transfection_machine transfection drug_selection Tcruzi_sample location has_agent is_a has_participant has_parameter has_participant PROVENIR ONTOLOGY PROVENIR ONTOLOGY PARASITE EXPERIMENT ONTOLOGY PARASITE EXPERIMENT ONTOLOGY *Parasite Experiment ontology available at:

Outline Provenance – Introduction Provenance Representation Classification of Provenance Queries & Query Operators Provenance Query Engine T.cruzi SPSE Provenance Management System 8

Provenance Query Classification Classified Provenance Queries into Three Categories Type 1: Querying for Provenance Metadata o Example: Which gene was used create the cloned sample with ID = 65? Type 2: Querying for Specific Data Set o Example: Find all knockout construct plasmids created by researcher Michelle using “Hygromycin” drug resistant plasmid between April 25, 2008 and August 15, 2008 Type 3: Operations on Provenance Metadata o Example: Were the two cloned samples 65 and 46 prepared under similar conditions – compare the associated provenance information 9

Provenance Query Operators Four Query Operators – based on Query Classification provenance () – Closure operation, returns the complete set of provenance metadata for input data entity provenance_context() - Given set of constraints defined on provenance, retrieves datasets that satisfy constraints provenance_compare () - adapt the RDF graph equivalence definition provenance_merge () - Two sets of provenance information are combined using the RDF graph merge 10

Outline Provenance – Introduction Provenance Representation Classification of Provenance Queries & Query Operators Provenance Query Engine T.cruzi SPSE Provenance Management System 11

Provenance Query Engine Support Provenance Query Operators over a RDF store Provenance Query Engine based on Jena plug-in for Oracle RDF store (support for SPARQL specification) Developed as an API, compatible with any RDF store with support for Rules Maps Query Operators to Domain-specific Provenance ontology – uses RDFS Entailment Rules Query Optimization: Defined a new class of materialized views called Materialized Provenance Views (MPV) MPV defined by Provenir ontology 12

Outline Provenance – Introduction Provenance Representation Classification of Provenance Queries & Query Operators Provenance Query Engine T.cruzi SPSE Provenance Management System 13

T.cruzi SPSE Provenance Management System 14

Conclusions A Common Model of Provenance – Interoperable, Consistent Interpretation and well- defined Semantics Categorization of Provenance Queries – Query Operators Provenance Query Engine Application of Provenance Metadata beyond Verification and Validation – eScience Data Management PROVENANCE ALGEBRA PROVENANCE ALGEBRA MATERIALIZED PROVENANCE VIEW MATERIALIZED PROVENANCE VIEW 15

Acknowledgement D. Brent Weatherly – Tarleton Lab, University of Georgia Flora Logan – The Wellcome Trust Sanger Institute Roger Barga – Microsoft Research Jonathan Goldstein – Microsoft Research Raghava Mutharaju – Kno.e.sis Center, Wright State University Pramod Anantharam - Kno.e.sis Center, Wright State University 16

More Resources at: Satya S. Sahoo et. al, "Where did you come from...Where did you go?" An Algebra and RDF Query Engine for Provenance, ( Trykipedia: A Wiki-based public resource for Parasite Researchers Provenance Management Framework: prov/ prov/ T.cruzi Semantic Problem Solving Environment: ife_sci/tcruzi_pse/ ife_sci/tcruzi_pse/ 17