Metadata Driven Integrated Statistical Data Management System Norberts
Metadata Driven Integrated Statistical Data Management System Norberts Talers
Outline - Integrated statistical data management system (ISDMS) history; - Main characteristics; - Principles of operation. Norberts Talers, ESRA 2015
ISDMS timeline, main milestones 1997 - 1999 • Initial Technical specification preparation • Theoretical basis – professor Bo Sundgren approach to information systems architecture in NSIs’ 2000 - 2002 • Development of the first version of the system –business statistics surveys, questionnaire based data collection 2002 2005 2009 – 2011 NOW • Launch of the system with 25 surveys fully operational (now – 120+ surveys) • Electronic data collection subsystem e-Survey launched with 2 surveys (now 100+ surveys) • Technical specification preparation and system development for Computer Assisted Survey Information segment – social and agricultural statistics surveys, interviewer based survey data collection • Possibility to collect and process data for virtually any survey • Standard data collection environment from respondents for CSB of Latvia Norberts Talers, ESRA 2015
ISDMS main aspects - standardized; integrated; meta data-driven; allows automated generation of user application forms (including for web); centralized; has a modular structure; transparent; Increase efficiency of the production of statistical information; Avoid hard code programming via standardisation of procedures and use of meta data within the statistical data processing; Increase the quality of the information produced. Norberts Talers, ESRA 2015
ISDMS main aspects, cont. -common data processing system at CSB of Latvia -technological enabler for processes standardization -completely metadata driven – no programming required to start up data collection of any survey Questionnaire description via metadata Survey generation Data analysis Respondent list management, preprint Data aggregation Data collection & entry Output tables generation Norberts Talers, ESRA 2015 Data validation Data dissemination
ISDMS, questionnaire preparation Business Statistics questionnaire Classification of Statistical Activities Social Statistics questionnaire INDICATORS Questionnaire Version Attributes Structure of questionnaire (layout) VARIABLES Data matrix, open tables (rows/columns) Types: Numeric, question, text, date, classifier (code tables) Structure of questionnaire Questions and Data matrix (rows/columns) METADATA REPOSITORY Routing of Questions Forms generation for keyboard entry (from paper survey, e-survey, CATI, CAPI, CAWI) Raw micro data Business Statistics Validation and deriving rules for Social Statistics Raw micro data Social Statistics Validations procedures generation for on-line and off-line validations Data analyse, editing and imputations Clean consolidate Micro data for Business Statistics Norberts Talers, ESRA 2015 Clean consolidate Micro data for Social Statistics
ISDMS, metadata base Norberts Talers, ESRA 2015
Example of validation Norberts Talers, ESRA 2015
Example of validation, cont. Norberts Talers, ESRA 2015
ISDMS functional structure Central part of system • Metadata description and analysis module • Data entry and validation module • CATI data entry • Business and Intrastat registers • Data analysis module • Data aggregation and retrieval module • Output tables generation module • Import / export facilities • Archiving • Respondent management module • User administration module e-Survey subsystem • Electronic questionnaire submission for business statistics CAPI subsystem • Interviewer based data collection CAWI subsystem • Electronic questionnaire submission for social statistics Norberts Talers, ESRA 2015
ISDMS and GSBPM Norberts Talers, ESRA 2015
Thanks for the attention! Norberts Talers, Norberts. Talers@csb. gov. lv
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