slide1
Download
Skip this Video
Download Presentation
Provenance Management Framework

Loading in 2 Seconds...

play fullscreen
1 / 17

Provenance Management Framework - PowerPoint PPT Presentation


  • 100 Views
  • Uploaded on

Provenance Management Framework. Satya S. Sahoo Kno.e.sis Center, Wright State University In Collaboration with Tarleton Lab, University of Georgia and Microsoft Research http://knoesis.wright.edu/research/semsci/application_domain/sem_prov /. Outline. Provenance – Introduction

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about ' Provenance Management Framework' - wyman


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
slide2

Provenance Management Framework

Satya S. Sahoo

Kno.e.sis Center, Wright State University

In Collaboration with Tarleton Lab, University of Georgia and Microsoft Research

http://knoesis.wright.edu/research/semsci/application_domain/sem_prov/

outline
Outline
  • Provenance – Introduction
  • Provenance Representation
  • Classification of Provenance Queries & Query Operators
  • Provenance Query Engine
  • T.cruzi SPSE Provenance Management System
provenance introduction
Provenance – Introduction

Gene Name

  • 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

Gene Knockout and Strain Creation*

Sequence

Extraction

3‘ & 5’

Region

Drug Resistant Plasmid

Gene Name

Plasmid

Construction

Knockout Construct Plasmid

T.Cruzi sample

?

Transfection

Transfected Sample

Drug

Selection

Cloned Sample

Selected Sample

Cell

Cloning

Cloned

Sample

*T.cruzi Semantic Problem Solving Environment Project, Courtesy of D.B. Weatherly and Flora Logan, Tarleton Lab, University of Georgia

outline1
Outline
  • Provenance – Introduction
  • Provenance Representation
  • Classification of Provenance Queries & Query Operators
  • Provenance Query Engine
  • T.cruzi SPSE Provenance Management System
provenir ontology
Provenir ontology

Gene Name

  • 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

Sequence

Extraction

contained_in

3‘ & 5’

Region

Drug Resistant Plasmid

AGENT

Plasmid

Construction

Knockout Construct Plasmid

T.Cruzi sample

has_agent

Transfection

Transfection Machine

DATA

Transfected Sample

Drug

Selection

participates_in

Selected Sample

PROCESS

Cell

Cloning

Cloned

Sample

domain specific provenance parasite experiment ontology
Domain-specific Provenance: Parasite Experiment ontology

PROVENIR

ONTOLOGY

agent

has_agent

is_a

is_a

data

parameter

has_participant

is_a

data_collection

is_a

process

is_a

spatial_parameter

temporal_parameter

domain_parameter

is_a

is_a

is_a

is_a

is_a

is_a

transfection_machine

location

is_a

drug_selection

is_a

is_a

sample

has_participant

Time:DateTimeDescritption

transfection

cell_cloning

is_a

transfection_buffer

strain_creation_

protocol

Tcruzi_sample

PARASITE

EXPERIMENT

ONTOLOGY

has_parameter

*Parasite Experiment ontology available at: http://wiki.knoesis.org/index.php/Trykipedia

outline2
Outline
  • Provenance – Introduction
  • Provenance Representation
  • Classification of Provenance Queries & Query Operators
  • Provenance Query Engine
  • T.cruzi SPSE Provenance Management System
provenance query classification
Provenance Query Classification

Classified Provenance Queries into Three Categories

  • Type 1: Querying for Provenance Metadata
    • Example: Which gene was used create the cloned sample with ID = 65?
  • Type 2: Querying for Specific Data Set
    • Example: Find all knockout construct plasmids created by researcher Michelle using “Hygromycin” drug resistant plasmid betweenApril 25, 2008 and August 15, 2008
  • Type 3: Operations on Provenance Metadata
    • Example: Were the two cloned samples 65 and 46 prepared under similar conditions – compare the associated provenance information
provenance query operators
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
outline3
Outline
  • Provenance – Introduction
  • Provenance Representation
  • Classification of Provenance Queries & Query Operators
  • Provenance Query Engine
  • T.cruzi SPSE Provenance Management System
provenance query engine
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
outline4
Outline
  • Provenance – Introduction
  • Provenance Representation
  • Classification of Provenance Queries & Query Operators
  • Provenance Query Engine
  • T.cruzi SPSE Provenance Management System
conclusions
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

MATERIALIZED

PROVENANCE

VIEW

acknowledgement
Acknowledgement
  • D. Brent Weatherly – Tarleton Lab, University of Georgia
  • Flora Logan – The Wellcome Trust Sanger Institute
  • Roger Barga– Microsoft Research
  • Jonathan Goldstein – Microsoft Research
  • RaghavaMutharaju– Kno.e.sis Center, Wright State University
  • PramodAnantharam- Kno.e.sis Center, Wright State University
more resources at
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, (http://knoesis.wright.edu/library/resource.php?id=00706)
  • Trykipedia: A Wiki-based public resource for Parasite Researchers http://knoesis.wright.edu/trykipedia
  • Provenance Management Framework: http://knoesis.wright.edu/research/semsci/application_domain/sem_prov/
  • T.cruzi Semantic Problem Solving Environment: http://knoesis.wright.edu/research/semsci/application_domain/sem_life_sci/tcruzi_pse/
ad