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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.

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

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  1. 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

  2. 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

  3. 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

  4. 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

  5. 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

  6. Challenges Approved for Public Release 11-412

  7. 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

  8. 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

  9. 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

  10. 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

  11. www.nga.mil Approved for Public Release 11-412

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