Implementing a Big Data strategy in the European Statistical System - - PowerPoint PPT Presentation

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Implementing a Big Data strategy in the European Statistical System - - PowerPoint PPT Presentation

Implementing a Big Data strategy in the European Statistical System Pieter Everaers , Director Cooperation in the European Statistical System; International Cooperation, Eurostat S PECIAL SESSION ON SHOWCASING BIG DATA Bangkok, Thailand Eurostat


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Implementing a Big Data strategy in the European Statistical System

Pieter Everaers,

Director Cooperation in the European Statistical System; International Cooperation, Eurostat SPECIAL SESSION ON SHOWCASING BIG DATA Bangkok, Thailand

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Eurostat / ESS experience

  • High level actionable commitment
  • Engage stakeholders within the European Commission
  • Raising awareness within Eurostat and the ESS
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ESS

  • Scheveningen Memorandum on Big Data
  • Eurostat Task Force Big Data and ESS task force Big Data
  • Big Data Roadmap and Action Plan 1.0
  • Big data Vision Implementation Project
  • Legal, ethical aspects, communication, skills and training,

information exchange

  • ESS Pilots

Engage stakeholders

  • European Commission Communication
  • "Towards a thriving data driven economy"

Implementation of ESS Vision 2020

  • Big Data roadmap and action plan integral part of portfolio

Current state

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  • Examine the potential of Big Data sources for official statistics
  • Official Statistics Big Data strategy as part of wider government

strategy

  • Address privacy and data protection
  • Collaboration at European and global level
  • Address need for skills
  • Partnerships

between different stakeholders (government, academics, private sector)

  • Developments in methodology, quality assessment and IT
  • Adopt action plan and roadmap for the European Statistical

System

Scheveningen Memorandum

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Roadmap

"As is" versus "To be"

Long term Vision Medium term aims Short term objectives

BY 2016 BY 2020 > 2020

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Short-term objectives

  • Official statistics integrated in the Commission big data strategy
  • Identification and analysis of output portfolio of big data

sources

  • Pilot projects
  • Skills and ESS professional training programmes are established
  • Research lines on big data included into the 2016-2017 Work

Programme of the Horizon 2020 Research Framework Programme

  • Communication to the general public on big data activities
  • Exchange of information with stakeholders within the

statistical system and the research community

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Medium-term objectives

  • Official Statistics integrated in governmental big data

strategies at national levels across the ESS

  • Pilots are finalised
  • Adequate IT infrastructures and methodological and quality

frameworks are available, data science skills integral part of

  • fficial statistics education
  • Public Private Partnerships are in place on big data and

Official Statistics.

  • Ethical guidelines and communication strategy
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Long-term objective

  • Big data sources integrated in ESS official statistics

production

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Experience sharing Policy Legislation Quality Skills Methodology IT Infrastructure Ethics / Communication P I L O T S

The ESS Big Data Action Plan

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Communication

Mobile phone data Social Media

WWW

Web Searches Businesses' Websites E-commerce websites Job advertisements Real estate websites

Sensors

Traffic loops Smart meters Vessel Identification Satellite Images

Process generated data

Flight Booking transactions Supermarket Cashier Data Financial transactions

Crow d sourcing

Volunteered geographic information (VGI) Community pictures collection

The ESS Big Data Action Plan

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Blending of Sources and multipurpose Statistics

Mobile Phone Data

Tourism Statistics Population Statistics Migration Statistics Traffic Statistics Commuting Statistics

Population Statisics

Mobile phone data Smart Meters VGI w ebsites Satellite Images

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  • Risks identified in the Action Plan and Roadmap
  • Difficult access to data
  • Negative public perception
  • Skill shortages
  • Eurostat suggested approach
  • Structuring risks and solutions
  • Analysis based on a quality framework
  • Collection of additional risks via survey among experts
  • Likelihood and Impact of risks by source

Risks in the use of big data for producing official statistics

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  • Engage the stakeholders within the European Commission
  • Cooperation at International level
  • Competition (Nowcasting)
  • Hackathons

Raising awareness

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Engage stakeholders within the European Commission

  • Data, Information and Knowledge Management at the

European Commission

  • Active cooperation with several policy DGs
  • Recognising a central role for the ESS
  • Towards a common Big Data Strategy supported by

appropriate IT infrastructure and skills

  • Data4Policy inter-departmental group
  • Applications oriented interdepartmental group
  • Fostering collaboration with policy departments and the

Joint Research Center (JRC) on concrete applications of using big data for policy.

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  • High-Level Group for the Modernisation of Statistical Production

and Services, Task Teams working on:

  • Pilots
  • Indicators for monitoring Sustainable Development Goals
  • Advocacy and Communication
  • Access and Partnerships
  • Quality, Methodology, Taxonomy
  • Inventory
  • Collaboration with the UNECE
  • Sandbox environment

Global Working Group on Big Data for Official Statistics

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Format

  • Collect predictions before official release is out. Repeat for

several periods and finally compare performance. Purpose

  • Provides an evaluation forum for methods and sources and

their applicability for statistical purposes

  • Raise awareness within the scientific community of problems

faced by the statistical system Application domains

  • Any statistical indicator which is frequent and stable enough

can be used including SDG related ones Expected launch: Autumn 2015

Competition (Nowcasting)

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Hackathons

Format and purpose

  • Get together for a day (or a night) or two, work intensely
  • n a problem
  • Get to know about specific problems, get to know people,

come up with innovative solutions

  • Traditionally done in computer science

Application domains

  • For Eurostat it was nowcasting unemployment with data

from Google Trends

  • Many other possibilities exist including SDG related

indicators

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  • Data flows instead of surveys and censuses
  • Data customer instead of data provider
  • Product designers instead of data collection designers
  • New answers related to
  • Quality and transparency
  • Privacy and confidentiality
  • Access to third party data sources / data sharing
  • Scientific standards and methodology
  • Professional ethics
  • Skills
  • Accreditation and certification instead of production
  • Embedded in data flow – statistics 'everywhere'

The statistical office of the future