Modernization of official statistics Eric Hermouet Statistics Division, ESCAP

Slides:



Advertisements
Similar presentations
United Nations Economic Commission for Europe Statistical Division Towards a Generic Statistical Business Process Model Steven Vale, UNECE.
Advertisements

United Nations Economic Commission for Europe Statistical Division Exploring the relationship between DDI, SDMX and the Generic Statistical Business Process.
United Nations Economic Commission for Europe Statistical Division The Data Deluge: What Does It Mean for Official Statistics? Steven Vale UNECE
United Nations Economic Commission for Europe Statistical Division Towards a Generic Statistical Business Process Model Steven Vale, UNECE.
GSIM, CSPA, and Related Activities of the High-Level Group
United Nations Economic Commission for Europe Statistical Division High-Level Group Achievements and Plans Steven Vale UNECE
United Nations Economic Commission for Europe Statistical Division Standards-based Modernisation An update on the work of the High-level Group for the.
United Nations Economic Commission for Europe Statistical Division Applying the GSBPM to Business Register Management Steven Vale UNECE
CES 2012 Paris 1 High Level Group for Strategic Developments in Business Architecture in Statistics Strategy Gosse van der Veen, Statistics Netherlands.
Background Defining and mapping business processes in statistical organisations started at least 10 years ago –“Statistical value chain” –“Survey life-cycle”
WP.5 - DDI-SDMX Integration E.S.S. cross-cutting project on Information Models and Standards Marco Pellegrino, Denis Grofils Eurostat METIS Work Session6-8.
Generic Statistical Information Model (GSIM) Thérèse Lalor and Steven Vale United Nations Economic Commission for Europe (UNECE)
TURKISH STATISTICAL INSTITUTE Workshop on International Collaboration for Standards-Based Modernisation Geneva, May 2015 Process oriented approach.
A perspective from beyond the ESS Alistair Hamilton Director – Statistical Information Standards Australian Bureau of Statistics.
M ETADATA OF NATIONAL STATISTICAL OFFICES B ELARUS, R USSIA AND K AZAKHSTAN Miroslava Brchanova, Moscow, October, 2014.
SDMX and DDI Working Together Technical Workshop 5-7 June 2013
Eszter Horvath United Nations Statistics Division Qatar National Statistics Day Doha, Qatar, 10 December 2013 Modernization of Official Statistics (Session.
Introduction and key issues identified in the papers UNECE Conference of European Statisticians June 2015 Second Seminar, Session I.
The Approach and ideas of the HLG-BAS: Modernizing Official Statistics.
Background to the Generic Statistical Information Model (GSIM) Briefing Pack December
Development of metadata in the National Statistical Institute of Spain Work Session on Statistical Metadata Genève, 6-8 May-2013 Ana Isabel Sánchez-Luengo.
Overview of quality work in Statistics Denmark Kirsten Wismer.
Population Census carried out in Armenia in 2011 as an example of the Generic Statistical Business Process Model Anahit Safyan Member of the State Council.
Second meeting 16 July 2014, Bangkok
Luisa Franconi Integration, Quality, Research and Production Networks Development Department Unit on microdata access ISTAT Essnet on Common Tools and.
United Nations Economic Commission for Europe Statistical Division Introducing the GSBPM Steven Vale UNECE
Explaining the statistical data warehouse (S-DWH)
United Nations Economic Commission for Europe Statistical Division Standards and Statistical Production Architectures Steven Vale UNECE
United Nations Economic Commission for Europe Statistical Division Mapping Data Production Processes to the GSBPM Steven Vale UNECE
United Nations Economic Commission for Europe Statistical Division High-Level Group Achievements and Plans Steven Vale UNECE
Statistical Metadata Strategy and GSIM Implementation in Canada Statistics Canada.
Process Description and Quality Guidelines – Two Birds with One Stone European Conference on Quality in Official Statistics Q2014 Rudi Seljak, Tina Steenvoorden.
1 High-Level Group for the Modernisation of Statistical Production and Services Annual Workshop Gosse van der Veen, Statistics Netherlands 2013 Geneva.
Eurostat SDMX and Global Standardisation Marco Pellegrino Eurostat, Statistical Office of the European Union Bangkok,
1 Modernization of Statistical Production and Services in Asia-Pacific Marko Javorsek, Statistics Division, ESCAP International Seminar on Modernizing.
SDMX IT Tools Introduction
Modernisation Activities DIME-ITDG – February 2015 Item 7.
Aim: “to support the enhancement and implementation of the standards needed for the modernisation of statistical production and services”
Stefan Schweinfest Acting Director, United Nations Statistics Division International Seminar on Modernizing Official Statistics: Meeting Productivity and.
Generic Statistical Information Model (GSIM) Jenny Linnerud
GSBPM and GAMSO Steven Vale UNECE
GSIM, DDI & Standards- based Modernisation of Official Statistics Workshop – DDI Lifecycle: Looking Forward October 2012.
United Nations Economic Commission for Europe Statistical Division Standards-based Modernization of Official Statistics Steven Vale UNECE
United Nations Economic Commission for Europe Statistical Division Enhanced Generic Models to Support the Standardisation of Statistical Production Steven.
ESS-net DWH ESSnet on microdata linking and data warehousing in statistical production.
United Nations Economic Commission for Europe Statistical Division The High-Level Group: Modernisation of Statistical Production and Services Steven Vale.
United Nations Economic Commission for Europe Statistical Division What’s New from the High-Level Group? Steven Vale UNECE
Advancing statistics for development Marko Javorsek ESCAP Statistics Division Modernization Working Group on Production, Methods, and Standards (MWG) First.
Statistical process model Workshop in Ukraine October 2015 Karin Blix Quality coordinator
United Nations Economic Commission for Europe Statistical Division GSBPM in Documentation, Metadata and Quality Management Steven Vale UNECE
United Nations Economic Commission for Europe Statistical Division Standards-based Modernisation Steven Vale UNECE
4–6 September 2013, Vilnius, Lithuania High-Level Seminar for Eastern Europe, Caucasus and Central Asia Countries QUALITY FRAMEWORK AT.
United Nations Economic Commission for Europe Statistical Division Achievements and Plans of the High-Level Group for the Modernisation of Official Statistics.
Contents Introducing the GSBPM Links to other standards
Strategic vision of the HLG-BAS High-Level Group on Strategic Developments in Business Architecture in Statistics Steven Vale UNECE
Generic Statistical Business Process Model GSBPM
GSBPM, GSIM, and CSPA.
Scanning the environment: The global perspective on the integration of non-traditional data sources, administrative data and geospatial information Sub-regional.
Applying the Generic Statistical Business Process Model to Business Register Maintenance Steven Vale UNECE
Modernization of Statistical data processes
Statistical Information Technology
Strategic vision of the HLG-BAS High-Level Group on Strategic Developments in Business Architecture in Statistics Steven Vale, UNECE With input from.
The Generic Statistical Business Process Model
Introducing the GSBPM Steven Vale UNECE
Contents Introducing the GSBPM Links to other standards
Mapping Data Production Processes to the GSBPM
Future Work Steven Vale UNECE
The Generic Statistical Business Process Model Steven Vale, UNECE
process and supporting information
High-Level Group for the Modernisation of Official Statistics
Presentation transcript:

Modernization of official statistics Eric Hermouet Statistics Division, ESCAP

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

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

The data deluge 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

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? 5

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 6

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 Statistics7

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 G eneric S tatistical B usiness P rocess M odel G eneric S tatistical I nformation M odel S tatistical D ata and M etadata e X change D ata D ocumentation I nitiative 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

15

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 16

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 18

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 19

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 20

Civil Registration and Vital Statistics21 Leads to a modular approach in designing software Plug and play tools

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  Civil Registration and Vital Statistics22

Further information  GSBPM – Generic+Statistical+Business+Process+Modelhttp://www1.unece.org/stat/platform/display/metis/The+ Generic+Statistical+Business+Process+Model  GSIM – ric+Statistical+Information+Model+(GSIM) ric+Statistical+Information+Model+(GSIM)  HLG-BAS – 23

THANK YOU. Questions? Civil Registration and Vital Statistics24