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Six Provocations of BIG DATA

Six Provocations of BIG DATA. Joe Howell • MCDM Cohort 12 Digital Democracy• August 11, 2012. IN 2000 THE WORLD GENERATED TWO EXABYTES OF NEW INFORMATION. Sources: “How Much Information?” Peter Lyman and Hal Varian, UC Berkeley, 2011 IDC Digital Universe Study. 2011.

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Six Provocations of BIG DATA

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  1. Six Provocations ofBIG DATA • Joe Howell • MCDM Cohort 12 • Digital Democracy• August 11, 2012

  2. IN 2000 THE WORLD GENERATED TWO EXABYTES OF NEW INFORMATION Sources: “How Much Information?” Peter Lyman and Hal Varian, UC Berkeley, 2011 IDC Digital Universe Study.

  3. 2011 IN 2000 THE WORLD GENERATED TWO EXABYTES OF NEW INFORMATION 5 EVERY DAY Sources: “How Much Information?” Peter Lyman and Hal Varian, UC Berkeley, 2011 IDC Digital Universe Study.

  4. big•data \ datasets so large theybreak traditionalIT infrastructures.

  5. What’s Driving The Data Deluge? Mobile Sensors Social Media Video Surveillance Video Rendering OilExploration Smart Grids Medical Imaging Gene Sequencing COST TO SEQUENCE ONE GENOME HAS FALLEN FROM $100M IN 2001 TO $10K IN 2011 OIL RIGS GENERATE 25000DATA POINTS PER SECOND READING SMART METERSEVERY 15 MINUTES IS 3000X MORE DATA INTENSIVE FACEBOOK UPLOADS 300 MILLION PHOTOS EACH DAY

  6. Six Provocations of Big Data

  7. Automating Research Changes the Definition of Knowledge. • Big Data creates a radical shift in how we think about research. • Big Data provides ‘destabilizing amounts of knowledge & information that lack the regulating force of philosophy. • Big Data is about exactly right now, with no historical context that is predictive. • Google and other harvesters of Big Data might change the meaning of learning.

  8. Claims to Objectivity and Accuracy are Misleading. • Big Data offers the humanistic disciplines a new way to claim the status of quantitative science. • Makes more social spaces quantifiable. • Big Data is subject to errors and researchers still have biases in interpretation. • Spectacular errors can emerge when researchers try to build social science findings into technological systems.

  9. Big Data are Not Always Better Data.

  10. Not All Data Are Equivalent 1 • Articulated Networks 2 Behavioral Networks 3 • Personal Networks

  11. Just Because It’s Accessible Doesn’t Make it Ethical. • What is the status of “public” data on social media sites? • Researchers cannot justify their actions as ethical just because data is accessible. • Are people who mine and analyze Big Data held to the same standard as academic researchers?

  12. Limited Access to Big Data Creates a New Digital Divide.

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