1. WP8 Methodology (SGA2)
Piet Daas
NL, AT, BG, IT, PT, PL, SL

2. Why Big Data? Possibilities: Shorter time to publication
Respond to current events
Higher reliability
More detail
More efficient processes
Considerations:
Competences
Culture
Methods
Quality
Infrastructure

3. SGA2: WP8 Methodology (and more)
WP8 is about:
Methodology
Quality IT
Goal is to generalize findings
What kind of methodology do we need when using Big Data for official statistics?
What kind of quality checks do we perform when using Big Data for official statistics?
What kind of IT-environment do we need when using for Big Data for official statistics?

4. A reflection A quote: “Big Data methodology does not exist”
Strange as a whole new approach was developed to process, check and edit road sensor data and estimate traffic intensities based on these
Conclusion:
Risk of to much ‘hearsay’
Risk of thinking in the old paradigm
All WP8 work should be fact based!
Use these facts to develop Big Data theory!

5. Starting point Start with the work done in SGA1 of ESSnet on Big Data
Interviewed:
WP1 Web scraping jobs
WP2 Web scraping enterprises
WP3 Smart meters
WP4 AIS
WP5 Mobile phones
WP6 Early estimates
WP7 Statistical domains (3 cases)

6. Next steps Input from any other work done
Are there Big Data based official statistics?
At least two examples
Scanner data based CPI
Traffic intensity statistics using road sensor data
Any more ..?
ESS VIP ADMIN findings ….
Keep the link with type of Big Data source in mind!
- Machine2machine, admin like, human derived (UN)
- Do they need different methods, quality checks, IT?

7. Combine all findings
After combining findings, organize the WP8 workshop
Invite WP8 members
Invite representatives of WP 1 t/m 7
Invite representatives from 22 partners involved (if not in 1 or 2)
Invite Eurostat representatives (if not in 1)
Invite experts not yet included (not in 1, 2, 3, 4)
(max of people)
Meet in person and discuss methodology, quality and IT in context of Big Data
Ultimate goal is to obtain consensus on these topics
(or at least narrow the field, focus is essential)

8. Output of WP8 Literature overview (month 5) Big Data and IT (month 9)
include most relevant Big Data studies
Big Data and IT (month 9)
Quality and Big Data (month 13)
Big Data Methodology (month 17)

9. Questions? 9

10. The Future
The
future of
statistics
looks
BIG

11. Thank you for your attention!
@pietdaas