United Nations Economic Commission for Europe Statistical Division High-Level Group Achievements and Plans Steven Vale UNECE

The story so far CSPA

New in 2014

Implementation of the CSPA

Services built 1. Seasonal adjustment – France, Australia, New Zealand 2. Confidentiality on the fly – Canada, Australia 3. SVG generator – OECD 4. SDMX transform – OECD 5. Sample selection – Netherlands 6. Linear error localisation – Netherlands 7. Linear rule checking – Netherlands 8. Error correction – Italy

Architecture Working Group Catalogue team **Just released**

Big Data

What does Big Data mean for official statistics? Priorities:  Partnerships – Guidelines  Privacy – Guidelines  Quality – Guidelines  Skills – Survey Skills profile  IT / methodological issues - Sandbox

Sandbox: Aims  Validate existing statistical standards / methods for use with Big Data  Big Data software tools – which ones are most useful for statistical organisations?  Feasibility of remote access and processing in the context of statistical production?  Develop an international collaboration community on the use of Big Data for statistics?

7 Sandbox Experiment Teams 75 Individuals from 25 countries / organisations 3 Task Teams Executive Board, Modernisation Committees 1 Project Manager 2 Coordinators Partners

Results

Some key outputs  Papers on “Machine learning” in statistical organisations Marketing official statistics Intellectual property Risk and change management  Generic Activity Model for Statistical Organisations (GAMSO)

GAMSO **Just released**

Big Data  More sandbox experiments  More data E.g. UNSD Comtrade  Future of the sandbox approach?  Challenge from the High-Level Group: Produce and release a set of internationally comparable statistics from one or more Big Data sources

CSPA Implementation  Specify together, develop individually  Catalogue release  Sustainable governance and support mechanisms  More CSPA services  Strategic investment plan Sprint, Canberra, March

Quality Management / Metadata Management Specify Needs DesignBuildCollectProcessAnalyseDisseminate 1.1 Identify needs 1.2 Consult & confirm needs 1.3 Establish output objectives 1.5 Check data availability 1.6 Prepare business case 2.1 Design outputs 2.4 Design frame & sample 2.3 Design data collection 2.5 Design processing & analysis 2.6 Design production systems & workflow 3.1 Build data collection instrument 3.2 Build or enhance process components 3.4 Configure workflows 3.5 Test production system 3.7 Finalize production system 4.1 Create frame & select sample 4.2 Set up collection 4.3 Run collection 4.4 Finalize collection 5.1 Integrate data 5.2 Classify & code 5.3 Review & validate 5.5 Derive new variables & units 5.7 Calculate aggregates 6.1 Prepare draft outputs 6.2 Validate outputs 6.3 Interpret & explain outputs 6.4 Apply disclosure control 6.5 Finalize outputs 7.1 Update output systems 7.2 Produce dissemination products 7.3 Manage release of dissemination products 7.5 Manage user support 7.4 Promote dissemination products 5.6 Calculate weights 1.4 Identify concepts Evaluate 8.1 Gather evaluation inputs 8.2 Conduct evaluation 8.3 Agree an action plan 5.4 Edit & impute 3.6 Test statistical business process 5.8 Finalize data files 2.2 Design variable descriptions 3.3 Build or enhance dissemination components ?

Other forthcoming events  9 March: Workshop on Big Data  April: Workshop on Modern- isation of Statistical Production  April: Workshop on Statistical Communication  29 April – 1 May: Workshop on Statistical Data Collection  5-7 May: Workshop on Standards-based Modernisation

Get involved! Anyone is welcome to contribute! Contact: More Information  HLG Wiki: www1.unece.org/stat/platform/display/hlgbas  LinkedIn group: “Modernising official statistics”