Generic Statistical Information Model (GSIM) Thérèse Lalor and Steven Vale United Nations Economic Commission for Europe (UNECE)

Slides:



Advertisements
Similar presentations
Summary of Participant Interview Themes for GSIM Sprint 1 7 February 2012.
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
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
Implementation of GSBPM, DDI and SDMX reference metadata at Statistics Denmark UNECE workshop 5-7 May 2015 Mogens Grosen Nielsen
GSBPM and GSIM as the basis for the Common Statistical Production Architecture Steven Vale UNECE
International Collaboration to Modernise Official Statistics
United Nations Economic Commission for Europe Statistical Division Standards-based Modernisation An update on the work of the High-level Group for the.
CES 2012 Paris 1 High Level Group for Strategic Developments in Business Architecture in Statistics Strategy Gosse van der Veen, Statistics Netherlands.
GSIM Stakeholder Interview Feedback HLG-BAS Secretariat January 2012.
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.
Statistics New Zealand Classification Management System Andrew Hancock Statistics New Zealand Prepared for 2013 Meeting of the UN Expert Group on International.
Eszter Horvath United Nations Statistics Division Qatar National Statistics Day Doha, Qatar, 10 December 2013 Modernization of Official Statistics (Session.
Generic Statistical Information Model (GSIM) Thérèse Lalor and Steven Vale United Nations Economic Commission for Europe (UNECE)
The Approach and ideas of the HLG-BAS: Modernizing Official Statistics.
Background to the Generic Statistical Information Model (GSIM) Briefing Pack December
 Metadata Technology North America  200 Prosperity Dr., Knoxville, TN USA  +1 (877) DDI – SDMX   Metadata Standards and Official.
United Nations Economic Commission for Europe Statistical Division Standards and Statistical Production Architectures Steven Vale UNECE
United Nations Economic Commission for Europe Statistical Division Introduction to Steven Vale UNECE
United Nations Economic Commission for Europe Statistical Division International Collaboration to Modernise Official Statistics Steven Vale UNECE
InSPIRe Australian initiatives for standardising statistical processes and metadata Simon Wall Australian Bureau of Statistics December
United Nations Economic Commission for Europe Statistical Division High-Level Group Achievements and Plans Steven Vale UNECE
The future of Statistical Production CSPA. 50 task team members 7 task teams CSPA 2015 project.
Eurostat SDMX and Global Standardisation Marco Pellegrino Eurostat, Statistical Office of the European Union Bangkok,
SDMX IT Tools Introduction
Modernisation Activities DIME-ITDG – February 2015 Item 7.
Modernization of official statistics Eric Hermouet Statistics Division, ESCAP
United Nations Economic Commission for Europe Statistical Division Data collection and the modernisation of official statistics Steven Vale UNECE
The use of GSIM in Statistics Norway Jenny Linnerud Senior Adviser Department of IT Statistics Norway 10th June 2014, Nizhny Novgorod.
Aim: “to support the enhancement and implementation of the standards needed for the modernisation of statistical production and services”
Generic Statistical Information Model (GSIM) Jenny Linnerud
Information about the HLG work Some considerations on HLG and related work from an NSI point of view Rune Gløersen, Statistics Norway.
GSBPM and GAMSO Steven Vale UNECE
Generic Statistical Data Editing Models (GSDEMs) Workshop on the Modernisation of Official Statistics The Hague, 24 November 2015.
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.
HLG MOS Flexibility and Adaptability HLG MOS Workshop November 24, 2015 The Hague Pádraig Dalton 1.
The future of Statistical Production CSPA. This webinar on CSPA (common statistical production architecture) is part of a series of lectures on the main.
United Nations Economic Commission for Europe Statistical Division GSBPM and Other Standards Steven Vale UNECE
The future of Statistical Production CSPA. We need to modernise We have a burning platform with: rigid processes and methods; inflexible ageing technology;
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
Achievements in 2016 Data Integration Linked Open Metadata
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
Introducing Statistical Standards -GAMSO
Methodology and Corporate Architecture
Generic Statistical Business Process Model (GSBPM)
GSBPM, GSIM, and CSPA.
GSIM The Generic Statistical Information Model
Scanning the environment: The global perspective on the integration of non-traditional data sources, administrative data and geospatial information Sub-regional.
The Generic Statistical Information Model
Modernising Official Statistics
International Collaboration to Modernise Official Statistics
The Generic Statistical Business Process Model
CSPA: The Future of Statistical Production
Introducing the GSBPM Steven Vale UNECE
Recent developments in the Generic Statistical Business Process Model: Revisions and Quality Indicators Alice Born, Statistics Canada,
Presentation to SISAI Luxembourg, 12 June 2012
SISAI STATISTICAL INFORMATION SYSTEMS ARCHITECTURE AND INTEGRATION
Generic Statistical Information Model (GSIM)
Introducing the Data Documentation Initiative
process and supporting information
GSIM overview Mauro Scanu ISTAT
Presentation transcript:

Generic Statistical Information Model (GSIM) Thérèse Lalor and Steven Vale United Nations Economic Commission for Europe (UNECE)

The Challenges Increasing cost & difficulty of acquiring data New competitors & changing expectations Rapid changes in the environment Competition for skilled resources Reducing budget Riding the big data wave

These challenges are too big for statistical organisations to tackle on their own. We need to work together

A High Level Group consisting of 10 heads of national and international statistical organizations was created Response from Official Statistics

Using common standards, statistics can be produced in a more efficient way No domain is special!

The GSBPM

The GSBPM is used by more than 50 statistical organizations worldwide to manage and document statistical production

GSIM is complementary to GSBPM Another model is needed to describe information objects and flows within the statistical business process

Introducing the GSIM You are here

What is GSIM? A reference framework of information objects It sets out definitions, attributes and relationships regarding information objects It aligns with relevant standards such as DDI and SDMX 11

Purposes of GSIM Improve communication Generate economies of scale Enable greater automation Provide a basis for flexibility and innovation Build staff capability by using GSIM as a teaching aid Validate existing information systems

GSIM is a conceptual model: It is a new way of thinking for statistical organizations

GSIM enables: Communication Coordination Cooperation Collaboration

Other relevant standards Geospatial standards DDI SDMX GSIM Conceptual model Implementation standards

17

CONCEPTS PRODUCTION BUSINESS STRUCTURES Statistical Need Business Case PopulationConcept Statistical Program Design changes design of Statistical Program Statistical Activity has includes Data Channel has Data Resource uses Process Step Data Set uses includes Unit Classification Variable Data Structure specifies Process output Process Input specifies has describes identifies defines measures defines is associated with comprises describes specifies may include may initiate comprises Acquisition Activity Production Activity Dissemination Activity initiates

GSIM: The “sprint’ approach The HLG-BAS decided to accelerate the development of the GSIM “Sprints” – 2 week workshops for experts (IT, methodology, statistics,...) Sprint 1 – Slovenia, February 2012 Sprint 2 – Republic of Korea, April 2012 Integration Workshop, Netherlands, September 2012

Moving to GSIM in practice GSIM could lead to: A foundation for standardized statistical metadata use throughout systems A standardized framework to aid in consistent and coherent design capture Increased sharing of system components

Moving to GSIM in practice Common terminology across and between statistical agencies. It allows NSIs and standards bodies, such as SDMX and DDI, to understand and map common statistical information and processes.

GSIM v1.0 Released in December 2012 We need people to use GSIM “in anger”. Then we will know how best to improve it.

More information GSIM c+Statistical+Information+Model+(GSIM) c+Statistical+Information+Model+(GSIM) Poster EDDI Today at lunch time