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CORE Demo Scenario Diego Zardetto , Istat & CBS CORE team

CORE Demo Scenario Diego Zardetto , Istat & CBS CORE team. Demo Scenario. Involves 3 typical processing steps performed by NSIs for sample surveys: Sample Allocation Sample Selection Estimation

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CORE Demo Scenario Diego Zardetto , Istat & CBS CORE team

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  1. CORE Final Meeting – 11 January 2012 CORE Demo Scenario Diego Zardetto, Istat & CBS CORE team

  2. CORE Final Meeting – 11 January 2012 Demo Scenario • Involves 3 typical processing steps performed by NSIs for sample surveys: • Sample Allocation • Sample Selection • Estimation • It has been used as empirical test-bed during the whole implementation cycle of the CORE environment

  3. CORE Final Meeting – 11 January 2012 Rationale for the Scenario • Minimality: very easy workflow (no conditionals, nor cycles), can be run without a Workflow Engine • Appropriateness: addresses heterogeneity issues • heterogeneity is precisely what CORE must be able to get rid of

  4. CORE Final Meeting – 11 January 2012 Spreading Heterogeneity over the Scenario • The Scenario incorporates both: • Data Heterogeneity: Via data exchanged by CORE services belonging to the scenario process • Technological Heterogeneity: Via IT tools implementing scenario services • A batch job based on a SAS script • Two full-fledged R-based systems

  5. CORE Final Meeting – 11 January 2012 The Scenario at a glance START ESTIMATION ALLOCATION MAUSS-R ReGenesees System SELECTION SAS SCRIPT STOP

  6. CORE Final Meeting – 11 January 2012 Sample Allocation Service • Overall Goal: determine the minimum number of units to be sampled inside each stratum, when lower bounds are imposed on the expected level of precision of the estimates the survey has to deliver • IT tool: Istat MAUSS-R system • implemented in R and Java • CORA tag: “Statistics” START ALLOCATION MAUSS-R

  7. CORE Final Meeting – 11 January 2012 Sample Selection Service • Goal: draw a stratified random sample of units from the sampling frame, according to the previously computed optimal allocation • IT tool: a simple SAS script to be executed in batch mode • CORA tag: “Population” SELECTION SAS SCRIPT

  8. CORE Final Meeting – 11 January 2012 Estimates and Errors Service • Goal: compute the estimates the survey has to provide (typically for different subpopulations of interest) along with the corresponding confidence intervals • IT tool: Istat ReGenesees System • R-based • CORA tag: “Statistics” ESTIMATION ReGenesees System STOP

  9. CORE Final Meeting – 11 January 2012 From the Scenario to the Demo

  10. Runtime Process Engine stratif errors frame estimates Estimation (ReGenesees) Allocation (MAUSS-R) Selection (SAS Script) bethel_out bethel_out sample sample CORE transformations CORE transformations xml xml

  11. Java/Webserver ISTAT stratif errors frame estimates Estimation (ReGenesees) Allocation (MAUSS-R) Selection (SAS Script) bethel_out bethel_out sample sample CORE transformations CORE transformations xml xml

  12. Bonita/Windows CBS stratif errors frame estimates Estimation (ReGenesees) Allocation (MAUSS-R) Selection (SAS Script) bethel_out bethel_out sample sample CORE transformations CORE transformations xml xml ISTAT

  13. CORE Final Meeting – 11 January 2012 Demo Details: Istat • What we are going to see: • A set of GUIs for process, services and data design • A set of GUIs for process execution

  14. CORE Final Meeting – 11 January 2012 Istat Demo back-end • What lies “behind” the GUIs • Integration API for CSV-CORE transformations • Core Repository • Data Flow Control System

  15. CORE Final Meeting – 11 January 2012 Demo Details: CBS • A process run executed via Bonita workflow engine

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