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Modernization of official statistics

Modernization of official statistics. Eric Hermouet Statistics Division, ESCAP hermouete.unescap@un.org. Changing environment. The data deluge New competitors Changing user demand Economic pressure. The data deluge. The internet had 1800 exabytes of data in 2011 exa = 10^18.

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Modernization of official statistics

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  1. Modernization of official statistics Eric HermouetStatistics Division, ESCAPhermouete.unescap@un.org

  2. Changing environment • The data deluge • New competitors • Changing user demand • Economic pressure

  3. The data deluge The internet had 1800 exabytes of data in 2011 exa = 10^18

  4. The data deluge 50 000 exabytes by 2020 Even if 99.9% are videos, photos, audio files, text messages etc., that still leaves a huge amount of potentially relevant data

  5. New competitors • Google: • Real-time price indices • Public Data Explorer • First point of reference for the “data generation” • Facebook, store cards, credit agencies, ... • What if they link their data? Can they provide an alternative to population censuses?

  6. Changing user demands • Statistics made available faster • Need to answer wider range of user • Need to package data differently • Need for more detailed information • Need for integrated data products • Linking logically datasets from different sources

  7. Response of official statistics community • Develop and promote new: Sources Processes Products • High-Level Group for Strategic Directions in Business Architecture in Statistics (HLG-BAS) • Created by the Conference of European Statisticians in 2010 • 9 heads of national and international statistical organizations Civil Registration and Vital Statistics

  8. The Challenges are too big for statistical organizations to tackle on their own. We need to work together • Collaboration • Coordination • Communication

  9. What is modernization? • Common processes • Common tools • Common methodologies • Recognizing that all statistics are produced in a similar way: No domain is “special” • Increased flexibility to adapt to new sources and produce new outputs

  10. Industry standards Generic Statistical Business Process Model Generic Statistical Information Model Statistical Data and Metadata eXchange Data Documentation Initiative

  11. GSBPM – The Background • Statistical production has traditionally been organised by topic, e.g. transport, trade, … • Some statistical organisations are moving towards a process-based approach

  12. GSBPM: Why do we need a model? • To define and describe statistical processes in a coherent way • To standardize process terminology • To compare and benchmark processes within and between organisations • To identify synergies between processes • To inform decisions on systems architectures and organisation of resources

  13. GSBPM: Applicability • All activities undertaken by producers of official statistics which result in data outputs • National and international statistical organisations • Independent of data source, can be used for: • Surveys / censuses • Administrative sources / register-based statistics • Mixed sources

  14. Key features of GSBPM • Not a linear model • Sub-processes do not have to be followed in a strict order • It is a matrix, through which there are many possible paths, including iterative loops within and between phases • Some iterations of a regular process may skip certain sub-processes

  15. Other uses of the GSBPM • Harmonizing statistical computing systems • Facilitating sharing of statistical software • Framework for process quality management • Structure for storage of documents • Measuring operational costs

  16. GSIM The Generic Statistical Information Model is a reference framework of information objects, which enables generic descriptions of data and metadata definition, management, and use throughout the statistical production process • Another model is needed to describe data and metadata objects and flows within the statistical business process

  17. GSIM • Provide a common reference model for statistical information • Define the information required to drive statistical production processes and define outputs • Facilitate building efficient metadata driven collection, processing, and dissemination systems

  18. Leads to a modular approach in designing software Plug and play tools Civil Registration and Vital Statistics

  19. Related ESCAP activities • EGM in June 2011 • SIAP Management Seminar in December 2011 • Moscow workshop, April 2012 • On the agenda of the upcoming Committee on Statistics, December 2012 • http://www.unescap.org/stat/MSIS/index.asp Civil Registration and Vital Statistics

  20. Further information • GSBPM • http://www1.unece.org/stat/platform/display/metis/The+Generic+Statistical+Business+Process+Model • GSIM • http://www1.unece.org/stat/platform/display/metis/Generic+Statistical+Information+Model+(GSIM) • HLG-BAS • http://www1.unece.org/stat/platform/display/hlgbas

  21. THANK YOU. Questions? Civil Registration and Vital Statistics

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