CORE Demo Scenario CORE Team Istat CBS CORE
CORE Demo Scenario CORE Team (Istat & CBS) CORE Final Meeting – 11 January 2012 1
Demo Scenario • Involves 3 typical processing steps performed by NSIs for sample surveys: ü Sample Allocation ü Sample Selection ü Estimation • It has been used as empirical test-bed during the whole implementation cycle of the CORE environment CORE Final Meeting – 11 January 2012 2
Rationale for the Scenario • Minimality: very easy workflow (no conditionals, nor cycles), can be run without a Workflow Engine • Appropriateness: addresses heterogeneity issues üheterogeneity is precisely what CORE must be able to get rid of CORE Final Meeting – 11 January 2012 3
Spreading Heterogeneity over the Scenario • The Scenario incorporates both: ü Data Heterogeneity: Via data exchanged by CORE services belonging to the scenario process ü Technological Heterogeneity: Via IT tools implementing scenario services – A batch job based on a SAS script – Two full-fledged R-based systems CORE Final Meeting – 11 January 2012 4
The Scenario at a glance START ALLOCATION ESTIMATION Re. Genesees System MAUSS-R SELECTION SAS SCRIPT CORE Final Meeting – 11 January 2012 STOP 5
Sample Allocation Service ALLOCATION START MAUSS-R • 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 ü implemented in R and Java • CORA tag: “Statistics” CORE Rome Meeting – 3/4 October 2011 6
SELECTION Sample Selection Service SAS SCRIPT • 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” CORE Final Meeting – 11 January 2012 7
ESTIMATION Estimates and Errors Service Re. Genesees System • Goal: compute the estimates the survey has to provide (typically for different subpopulations of interest) along with the corresponding confidence intervals • IT tool: Istat Re. Genesees System ü R-based STOP CORE Final Meeting – 11 January 2012 • CORA tag: “Statistics” 8
From the Scenario to the Demo CORE Final Meeting – 11 January 2012 9
Runtime Process Engine stratif errors frame Allocation (MAUSS-R) estimates Estimation (Re. Genesees) Selection (SAS Script) bethel_out CORE transformations xml sample CORE transformations xml
ISTAT stratif Java/Webserver errors frame Allocation (MAUSS-R) estimates Estimation (Re. Genesees) Selection (SAS Script) bethel_out CORE transformations xml sample CORE transformations xml
CBS stratif Bonita/Windows errors frame Allocation (MAUSS-R) Estimation (Re. Genesees) Selection (SAS Script) bethel_out CORE transformations ISTAT estimates xml sample CORE transformations xml
Demo Details: Istat • What we are going to see: üA set of GUIs for process, services and data design üA set of GUIs for process execution CORE Final Meeting – 11 January 2012 13
Istat Demo back-end • What lies “behind” the GUIs ü Integration API for CSV-CORE transformations ü Core Repository ü Data Flow Control System CORE Final Meeting – 11 January 2012 14
Demo Details: CBS • A process run executed via Bonita workflow engine CORE Final Meeting – 11 January 2012 15
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