Deep Web, Open Source Intelligence, and The Bad Guy

  • September 17, 2014 · 6:30 PM

Deep Web, Open Source Intelligence, and The Bad Guy

As Data Scientist, we are constantly asked to derive insights, in form of predictive and prescriptive models, from disparate sets of internal and external data. Of all the possible kinds of insights available, we are now seeing real business value from those that come in from Anticipatory Intelligence, which is actionable insights delivered through next best steps. While many think the real challenge is developing anticipatory intelligence is in their algorithms, the challenge in realizing reliable value is actually in complexity of disparate data sets themselves. In this discussion, we will explore how data science is impacted by one of the most complex data sets of all times, the deep web. In doing so we use an open source intelligence driven data science framework to explore dark kinetic world of anarchy (the deep dark web), while searching for one particular influential organization responsible for orchestrating violence amongst passive groups.

About the Presenter:

Dr. Jerry A. Smith is the Chief Data Scientist for Capgemini’s Advance Digital Intelligence (ADI) group and Data Science & Analytics (DSA) group. His work includes the develop of intelligence platforms that harvest the digital world through hadoop ecosystems, map reduce analytics, and distribute R predictive and prescriptive models. Dr. Smith also served in the United States Navy where he flew the A-6 Intruder and operated submarine-based nuclear reactors.

Data Scientist Insights: http://datascientistinsights.com


Extended Bio:

Dr. Jerry A. Smith is a visionary entrepreneurial data scientist with 16 years of machine learning, predictive modeling, digital and business analytics, big data, and enterprise data science experience. Jerry is recognized as a leading expert in simulation and modeling, leveraging Walsh-Hadamard transforms to identify spatial patterns in real-time temporal data. Over the last five years, he has worked on practical methods for unifying data science capabilities and big data infrastructure throughout the enterprise, in order to create organic and systemic Data Monetization capabilities.

He has created data Science practices, which focuses on helping companies realize actionable value from data and information sources - Data Monetization. Leveraging an Enterprise Data Science (EDS) methodology based on an hypotheses-driven framework, data science teams (data scientists and functional behavioral analysts) identify key business objectives, along with critical causal-levers that impact the value chain. Enterprise, IT, and third party data is inventoried and assessed for their causality and correlative characteristics. Exploratory visualization maps are created that lead to the design and development of predictive models. The models are aggregated into complex solution spaces; which represent comprehensive, cohesive predictive ecosystem. Using simulated annealing, optimal actionable structures are identified, which are implemented across their enterprise applications.

Dr. Smith is recognized as an technologist, innovator, and communicator: Technical evangelist to investors, stakeholders, and clients. Won major industry awards. Recognized for technology trend-setting prescience by Gartner & Ben Franklin Technology Partners. Excels at translating complex modeling into clear understandings. Cited by technology-oriented periodicals, industry reports, and media.



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  • Christine M.

    Thanks for posting the video of Dr J's talk - very interesting work.
    Wonderful write-up Jennifer Markert @Curiousmatic - thank you!

    1 · September 25

  • Jennifer M.

    This was my first Data Skeptics meetup, and I enjoyed it immensely! Dr J is an extremely intriguing and insightful character. If anyone is interested, and especially if you missed the lecture, I've published a write-up of the event for Curiousmatic.com. Check it out, and feel free to share or contact me! http://curiousmatic.com/data-skeptics-and-the-deep-web-the-explorations-of-a-data-scientist/

    3 · September 25

  • Mike

    That was a very interesting presentation. I recommend that everyone also read https://en.wikipedia.org/wiki/Demon_haunted_world by Carl Sagan. In this book, Sagan covers the connection between hallucinatory experiences, such as those in near-death experiences, and hunts for “bad guys”. One example given involves divine experiences in which one communicates with a deity, such as the Christian God, or one of its emissaries, and related personal and societal witch hunts. (continued in reply due to character limits)

    2 · September 17

    • Mike

      The “witch” can take many forms but at its basic can be described as “anyone not like me”, or in this presenter's case “anyone not on my side”. The “side” is determined either by personal reasons, in this case a family member's addiction, or to the highest bidder, such as the client who hired him to investigate Greenpeace Italia. The methods employed by the witch hunter are often pseudo- or proto-scientific and involve delving into some ethereal realm, in this case data science and the so-called “deep web” or “dark web”.

      Sagan also discusses the data surrounding actual bad guys, such as the given example of child sex traffickers, and the difficulty in distinguishing real from fabricated cases. Much more is covered by this book, and it's a great read for aspiring and seasoned critical thinkers alike. Personally, I think I'll stay away from the deeper depths of the Internet until there is more reliable information.

      2 · September 17

    • Gene M.

      I enjoyed this session a lot. The provocative ideas provided good exercises for critical thinking. Seemed appropriate for a Skeptics meetup.

      1 · September 19

  • Dr. Jerry A. S.

    Thanks you all for the opportunity to share some of my thoughts on this subject. While I think this is an interesting field of study, I am really glad to see that there are a few others that feel the same way.

    Cerca Trova,
    Jerry

    2 · September 19

  • Steve L.

    All, thanks for coming.

    We did video Jerry's talk and will make it available ASAP.

    2 · September 18

  • Allen W.

    Excellent presentation. Would be interesting to see if data is available, say about Identity theft, from European countries to determine if the the problems in the US social or structural?

    September 18

  • Cheryl S.

    The speaker was committed to extracting the secrets of the deep web. Great presentation.

    September 18

  • Cheryl S.

    The speaker was committed to extracting the secrets of the deep web. Great presentation.

    September 18

  • RahibeM

    This is was my first meetings; the presentation was awesome as well as the location. It will be great to see the video or the slides. Looking forward for the next meeting.

    September 18

  • Alex Stojcic (.

    What a mindblowing presentation! As Dr Smith put it im 1202'ing

    4 · September 17

    • Michael K.

      Thank you! Good to hear, hope to see it soon!

      1 · September 17

    • Patricia S.

      I would love to see the video! There was too much info to be sure I captured the details in just one iteration.

      1 · September 18

  • Patricia S.

    Fascinating. The best yet - and all previous meetings were great!

    September 18

  • avnerkam

    An excellent event! Thanks!

    1 · September 18

  • Gene M.

    Ironically, the brief description on this page reads as "Deep Web ... and The Bad Guy As Data Scientist ...". Only after clicking "see all" does it display the line break after "Bad Guy".

    September 18

  • Digant M.

    Great presentation!

    September 17

  • Michael K.

    I would be very happy to see audio/video/slides/whatever - very interesting talk!

    1 · September 17

  • Sanjay R.

    I have something else come up, is it possible to have this recorded for later viewing

    September 17

  • Candida H.

    This sounds amazing but I'm in Portland!

    September 17

  • Nitin k.

    This is a great topic. Will this event be recorded for people who may have last minute work and are unable to attend. Pl. let us know...

    2 · September 17

  • Nachiket P.

    Can't do Sept 17th. I really wish you have a podcast I can listen to later.

    September 9

  • Alan B.

    Can't do Wednesday. Oh well. Enjoy.

    August 18

  • Tendekai M.

    Was the date changed to September 18?

    July 22

  • Eugene Y.

    Big Data Analytics nabs 1,000 corrupt LIRR employees, 1 billion stolen. Was the data killed the beast.
    http://www.nydailynews.com/news/crime/lirr-doc-1-billion-scam-8-years-prison-article-1.1628516

    July 22

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