Omitola o rian_eswc_idts final
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This document discusses capturing interactive data transformations using provenance workflows. It presents a model for interactive data transformations (IDTs) involving user interactions. Challenges include representing IDTs and facilitating reuse. The approach models IDTs and represents provenance using the Open Provenance Model. It describes capturing provenance for IDTs during interactive sessions to provide transparency into the transformation process. A case study demonstrates implementing provenance for an IDT tool based on the Google Refine platform.
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![Case study
Digital Enterprise Research Institute www.deri.ie
Implementation over the GR Platform
Example descriptor
@prefix grf: <http://127.0.0.1:3333/project/1402144365904/> .
grf :MassCellChange-1092380975 rdf:type opmv:Process,
cogs:ColumnOperation, cogs:Transformation; Mapping to the actual program
cogs:operationName "MassCellChange"^^xsd:string;
cogs:programUsed "com.google.refine.operations.cell.MassEditOperation"^^xsd:string; Process
rdfs:label "Mass edit 1 cells in column ==List of winners=="^^xsd:string.
grf:MassCellChange-1092380975/1_0 rdf:type opmv:Artifact ; Input Artifact
rdfs:label "* '''1955 [[Meena Kumari]]'[[Parineeta (1953 film)|Parineeta]]''''' as '''Lolita'''"^^xsd:string.
grf:MassCellChange-1092380975/1_1 rdf:type opmv:Artifact; Output Artifact
rdfs:label "* '''John Wayne'''"^^xsd:string.
Workflow structure
grf:MassCellChange-1092380975/1_1 opmv:wasDerivedFrom grf:MassCellChange-1092380975/1_0.
grf:MassCellChange-1092380975 opmv:used grf:MassCellChange-1092380975/1_0.
grf:MassCellChange-1092380975/1_1 opmv:wasGeneratedBy grf:MassCellChange-1092380975.
grf:MassCellChange-1092380975/1_1 opmv:wasGeneratedAt "2011-11-16T11:2:14"^xsd: dateTime.](https://image.slidesharecdn.com/omitolaorianeswcidtsfinal-120530081633-phpapp02/85/Omitola-o-rian_eswc_idts-final-16-320.jpg)
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Omitola o rian_eswc_idts final
- 1. Digital Enterprise Research Institute www.deri.ie Capturing interactive data transformation operations using provenance workflows Tope Omitola, Andre Freitas, Edward Curry, Sean O'Riain, Nicholas Gibbins and Nigel Shadbolt SWPM Workshop 28.05.2012, Herakleion, Crete Copyright 2009 Digital Enterprise Research Institute. All rights reserved.
- 2. Outline Digital Enterprise Research Institute www.deri.ie Motivation Interactive data transformations (IDTs) IDT & Provenance Modelling IDTs Provenance Representation Provenance Capture Case Study Conclusion
- 3. Motivation Digital Enterprise Research Institute www.deri.ie Dataspaces: High number of heterogeneous data sources Complex data transformation environment Need for both repeatable data transformations and once- off transformations Traditional ETL approaches for data transformation/integration: Based on scripting/programming Focus on repeatable data transformation processes
- 4. Interactive Data Transformation (IDTs) Digital Enterprise Research Institute www.deri.ie Based on user interaction paradigms for user creation of data transformations Explores GUI elements mapping to data transformation operations Instant feedback of each iteration Complementary to existing ETL tools Lower the barriers for non-programmers (reduces programming effort) of doing data transformations Example platforms: Google Refine, Potters Wheel, Wrangler
- 5. Interactive Data Transformation (IDTs) Digital Enterprise Research Institute www.deri.ie
- 6. Challenges Digital Enterprise Research Institute www.deri.ie How to model IDTs? Facilitating the reuse of previous IDTs Representing IDTs Provenance Making IDT platforms provenance-aware Enabling transportability across IDT and ETL platforms
- 7. IDT & Provenance Digital Enterprise Research Institute www.deri.ie Provenance supports representation of interactive data transformations Output: a provenance descriptor which shows the relationship between the inputs, the outputs, and the applied transformation operations Both retrospective and prospective provenance
- 8. IDT Digital Enterprise Research Institute www.deri.ie IDT model Formal model (Algebra for IDT) Provenance representation Provenance capture of IDTs
- 9. IDT Model: Core Elements Digital Enterprise Research Institute www.deri.ie Schema and instance data Set of predefined operations GUI elements mapping to predefined operations User actions Operation selection Parameter selection Operation composition (workflow)
- 10. IDT Model Digital Enterprise Research Institute www.deri.ie
- 11. Formalizing the mapping from IDT to Provenance Digital Enterprise Research Institute www.deri.ie Definition 1: A provenance-based interactive data transformation engine, consists of a set of transformations (or activities) on a set of datasets generating outputs in the form of other datasets or events which may trigger further transformations Definition 2: An interactive data transformation event, consists of the input dataset, the output dataset(s), the applied transformation function, and the time the transformation took place
- 12. Formalizing the mapping from IDT to Provenance Digital Enterprise Research Institute www.deri.ie Definition 3: A run is a function from time to dataset(s) and the transformation applied to those dataset(s) Definition 4: A trace is the sequence of pairs of a run and the time the run was made
- 13. Provenance Representation Digital Enterprise Research Institute www.deri.ie Proposed in Representing Interoperable Provenance Descriptions for ETL Workflows Three-layered provenance model: Open Provenance Model Vocabulary Layer Cogs ETL Provenance Vocabulary Domain-Specific Model Layer Linked Data standards
- 14. Provenance Capture Layers Digital Enterprise Research Institute www.deri.ie
- 15. Provenance Event-Capture Sequence Flow Digital Enterprise Research Institute www.deri.ie
- 16. Case study Digital Enterprise Research Institute www.deri.ie Implementation over the GR Platform Example descriptor @prefix grf: <http://127.0.0.1:3333/project/1402144365904/> . grf :MassCellChange-1092380975 rdf:type opmv:Process, cogs:ColumnOperation, cogs:Transformation; Mapping to the actual program cogs:operationName "MassCellChange"^^xsd:string; cogs:programUsed "com.google.refine.operations.cell.MassEditOperation"^^xsd:string; Process rdfs:label "Mass edit 1 cells in column ==List of winners=="^^xsd:string. grf:MassCellChange-1092380975/1_0 rdf:type opmv:Artifact ; Input Artifact rdfs:label "* '''1955 [[Meena Kumari]]'[[Parineeta (1953 film)|Parineeta]]''''' as '''Lolita'''"^^xsd:string. grf:MassCellChange-1092380975/1_1 rdf:type opmv:Artifact; Output Artifact rdfs:label "* '''John Wayne'''"^^xsd:string. Workflow structure grf:MassCellChange-1092380975/1_1 opmv:wasDerivedFrom grf:MassCellChange-1092380975/1_0. grf:MassCellChange-1092380975 opmv:used grf:MassCellChange-1092380975/1_0. grf:MassCellChange-1092380975/1_1 opmv:wasGeneratedBy grf:MassCellChange-1092380975. grf:MassCellChange-1092380975/1_1 opmv:wasGeneratedAt "2011-11-16T11:2:14"^xsd: dateTime.
- 17. Conclusion Digital Enterprise Research Institute www.deri.ie The proposed approach provides low impact on the existing IDT process Provenance representation supports different data models Preliminary implementation of a Google Refine provenance extension