1. United Nations Economic Commission for Europe Statistical Division International Collaboration to Modernise Official Statistics Steven Vale UNECE steven.vale@unece.org

2. HLG Projects 2012 Generic Statistical Information Model 2013 Common Statistical Production Architecture Frameworks and Standards for Statistical Modernisation 2014 Implementation of the Common Statistical Production Architecture Big Data in Official Statistics

3. HLG 30+ Expert Groups Projects

4. Big Data

5. Background  HLG paper for 2013 CES Plenary Session “What does Big Data mean for official statistics?”  CES gave priority to work on: “facilitating the use of Big Data for official statistics”  Big Data is a priority project for 2014

6. In the last 2 years more information was created than in the whole of the rest of human history!

8. Project – Key themes  Strategic / methodological issues Identify Propose practical solutions  Sandbox Shared environment to test ideas  Training What should we know? Deadline – End of 2014!

9. The story so far...

10. Virtual Sprint  10 - 14 March  2 hour web conference every day for 4 days + 2 hours per day of offline work.  13 participants Australia, Canada, Ireland, Italy, Mexico, Netherlands, New Zealand, UK, US, Eurostat, OECD  Result: Paper on key issues

11. Physical sprint Consultation Virtual sprint Task teamsGuidelines

12. Physical Sprint  2 – 3 April, in Rome, hosted by Istat  15 participants Australia, Austria, Canada, Italy, Mexico, Netherlands, Poland, Sweden, United Kingdom, United States, Eurostat, UNECE

13. Sprint Outcomes  Key challenges identified: The need for a quality framework for Big Data Managing privacy and data security Developing partnerships with data suppliers, processors and users Developing methodology and IT for Big Data Developing the skills needed to use Big Data  Currently establishing task teams to tackle these issues Volunteers welcome!  Reports / guidelines by the end of 2014

14. Sandbox  Will be launched today! Irish Centre for High-End Computing / CSO have created a Big Data ‘sandbox’ containing datasets and tools

15. Sandbox: Aims  Test feasibility of remote access and processing: Could this approach be used in practice?  Test whether existing statistical standards / models / methods can be applied to Big Data  Determine which Big Data software tools are most useful for statistical organisations  Learn about the potential uses, advantages and disadvantages of Big Data – “learning by doing”.  Build an international collaboration community on the technical aspects of using Big Data

16. Working together for minimum cost and maximum benefit!

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