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Tipping Points, Butterflies, and Black Swans: A Vision for Spatio -temporal Data Mining Analysis Dr. James M. Kang and Daniel L. Edwards InnoVision Basic and Applied Research Office National Geospatial-Intelligence Agency August 24, 2011. Approved for Public Release 11-412. Vision.

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Tipping Points, Butterflies, and Black Swans: A Vision for Spatio -temporal Data Mining Analysis

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Tipping points butterflies and black swans a vision for spatio temporal data mining analysis

Tipping Points, Butterflies, and Black Swans: A Vision for Spatio-temporal Data Mining Analysis

Dr. James M. Kang and Daniel L. Edwards

InnoVision Basic and Applied Research Office

National Geospatial-Intelligence Agency

August 24, 2011

Approved for Public Release 11-412


Vision

Vision

  • The development of data mining and spatio-temporal analytical techniques to discover tipping-points, butterflies, and black swans.

Approved for Public Release 11-412


What are tipping points

What are Tipping Points?

  • “the moment of critical mass, the threshold, the boiling point” – M. Gladwell

Climate Tipping Point, Upsala Glacier, Patagonia, Argentina(Source: http://www.changeclimate.org/)

Approved for Public Release 11-412


What is the butterfly effect

What is the Butterfly Effect?

  • Behavior of dynamic systems

    • Highly sensitive to initial conditions – J. Gleck

    • Involve topologically mixing – B. Hasselblatt

Source: http://www.guardian.co.uk/world/interactive/2011/mar/22/middle-east-protest-interactive-timeline

Approved for Public Release 11-412


What are black swans

What are Black Swans?

  • Unpredictable patterns that do not appear to be Gaussian with an exponential diminishing tail, but a flatter curve with tails that are fatter

  • Have the following characteristics:

    • The event is a surprise (to the observer).

    • The event has a major impact.

    • After its first recording, the event is rationalized by hindsight, as if it could have been expected.

  • – N. Taleb

Approved for Public Release 11-412


Challenges

Challenges

Approved for Public Release 11-412


Tipping point challenges

Tipping Point Challenges

  • Assumptions about a dataset may change before and after a tipping point event

  • Tobler’s Law vs. Teleconnections

Approved for Public Release 11-412


Butterfly effect challenges

Butterfly Effect Challenges

  • Bounding problem with sufficiency

  • Depth – sufficient data to mine vs. scope of problem?

  • Breadth - breadth of data sufficient to sample problem?

  • Missing – key data/meta data missing?

  • Stability - of mined patterns?

Approved for Public Release 11-412


Black swan challenges

Black Swan Challenges

  • As a Black Swan unfolds,

    • Mined patterns over populations and time may not become “interesting”

    • May not be prevalent or anomalous

  • After a Black Swan is recognized (hindsight),

    • Bounding sufficiency may be too complex to overcome

    • May not generalize to other known black swans

Approved for Public Release 11-412


First and next steps

First and Next Steps

  • Tipping Points

    • Existing literature in abrupt changes, transitions, etc.

    • Transient vs. Persistent

  • Butterflies and Black Swans

    • Can these be generalized?

    • Are these even possible?

    • How can we begin quantifying these events?

  • Example Datasets

    • Guardian’s event dataset of middle-east

    • CIA World Factbook dataset

Source: https://www.cia.gov/library/publications/the-world-factbook/

Approved for Public Release 11-412


Tipping points butterflies and black swans a vision for spatio temporal data mining analysis

www.nga.mil

Approved for Public Release 11-412


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