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BigDataEurope - Big Data & Inclusive and Reflective Societies


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Big Data and the Inclusive/Reflective Societies domain (vis-a-vis the respective H2020 Societal Challenge) - Opportunities, Challenges and Requirements. As presented and discussed in the public launch of the BigDataEurope project.

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BigDataEurope - Big Data & Inclusive and Reflective Societies

  1. 1. Opportunities, Challenges and Requirements 27/02/2015 BIG DATA & INCLUSIVE AND REFLEXIVE SOCIETIES
  2. 2. Statistics and social sciences ...that’s useful...that’s pretty… > ….that’s trustworthy Current sources have strengths: Authenticity, reliability, replicability, comparability over space and time, and permanence in the public record. Methodology, sources, definitions, thesaurus, question banks, sample sizes, etc., specified in legislation, or established by international policy coordination.
  3. 3. Statistics and social sciences ...that’s useful...that’s pretty… > ….that’s trustworthy... But can be weak in coverage, timliness, cost, relevance. And vulnerable to Campbell’s law :
  4. 4. Statistics and social sciences Campbell’s law : "The more any quantitative social indicator (or even some qualitative indicator) is used for social decision-making, the more subject it will be to corruption pressures and the more apt it will be to distort and corrupt the social processes it is intended to monitor."
  5. 5. Drivers for exploring new Big Data sources Can Big Data tackle the weaknesses, yet maintain the strengths? Deal with the cost of conventional data collection? (€100 or more per household interview) Give new insight into new concepts? (eg. Wellbeing) Improve timeliness? (Google flu vs. doctors’ records vs death registrations)
  6. 6. A new tip for the triangle?
  7. 7. Awareness
  8. 8. Awareness UNECE High Level Group Project on Big Data. ESS Big Data event, Rome, March 2014 Eurostat Task Force - Big Data. "Scheveningen Memorandum", 09/ 2013 OECD Technology Foresight - Big Data as a new source of growth Administrative Data Research Network - UK
  9. 9. Awareness International Statistics Institute satellite meeting at UN Statistics Commission meeting, New York, 3 March 2015: ● a) How to ensure that use of non-traditional sources of data will not compromise the professional standards in statistics and risk decreasing public trust in statistical data and analyses either at the country, or international level? ● b) How to deal with privacy-efficiency trade-off in the context of greater access to administrative and Big Data sources? How we should address them?
  10. 10. Interdependencies Linked to Open Data and Visualisation tools - to public numeracy initiatives - Public participation in democracy - Trust agenda (ref. CRU at UEA climate data debacle)
  11. 11. Sledgehammer to crack a nut? Sometimes - but it may be the only way to open the nut… ONS used 2 months of Twitter’s tweets to validate which of the addresses in their database were residential. projects/the-ons-big-data-project/index.html
  12. 12. Sometimes the sledgehammer cracks a persistent nut...
  13. 13. What do we want? As data archive services, we need new capacity and new technology to provide our services to Big Data owners. Today, we don’t know how to deliver our mandate with respect to Big Data archiving and re-use.
  14. 14. What do we want?
  15. 15. What do we want?
  16. 16. What do we want?
  17. 17. What do we want?
  18. 18. What do we want? A place to import data, learn how to manage it, and help researchers experiment with it Help and support, to compare and contrast Examples and inspiration Some of our questions answered...
  19. 19. What do we want? - what does “archiving” mean in Big Data? - what is captured for reuse? - what services should social science archives offer? - how can we help achieve equality of access to this new evidence base for decision making?