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What is Data?


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What is Data?

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What is Data?

  1. 1. What is Data? An Existential [but useful] Exploration
  2. 2. “Russell Foltz-Smith” • Self Appointed Artist • Green Eyes, Red Head • 5’10”, 243lbs • 22 tattoos • Married, 2 kids • @UChicago Math BA • 43 Theater Shows • Son • 42 moves, 5 states Finance Developer Product, BI VP Product VP Tech, Content CTO Biz Dev President SVP, Data
  3. 3. In place of facts, we now live in a world of data. Instead of trusted measures and methodologies being used to produce numbers, a dizzying array of numbers is produced by default, to be mined, visualised, analysed and interpreted however we wish. If risk modelling (using notions of statistical normality) was the defining research technique of the 19th and 20th centuries, sentiment analysis is the defining one of the emerging digital era. We no longer have stable, ‘factual’ representations of the world, but unprecedented new capacities to sense and monitor what is bubbling up where, who’s feeling what, what’s the general vibe. Financial markets are themselves far more like tools of sentiment analysis (representing the mood of investors) than producers of ‘facts’. This is why it was so absurd to look to currency markets and spread-betters for the truth of what would happen in the referendum: they could only give a sense of what certain people at felt would happen in the referendum at certain times. Given the absence of any trustworthy facts (in the form of polls), they could then only provide a sense of how investors felt about Britain’s national mood: a sentiment regarding a sentiment. As the 23rd June turned into 24th June, it became manifestly clear that prediction markets are little more than an aggregative representation of the same feelings and moods that one might otherwise detect via twitter. They’re not in the business of truth-telling, but of mood-tracking. -Will Davies (
  4. 4. Data is. There exists data about everything and anything. Including data. Data is relational residue.
  5. 5. Data About Other Specific Data Types Specific Detectors
  6. 6. Data As Other. Organs – rendered data by 3d printers Surrealism turned real. Old Master Painters reanimated as New Master Data Scientists Interiors augmented. Weapons are just printed data.
  7. 7. Data As Detector Generalized DetectorsGeneralized Data Networks are DATA and DETECTOR.
  8. 8. Data As Complex Recursion (w. errors)Gene replication. Error Data is the animating aspect of evolution and learning. Printers Printing Printers Printing Printers… & All complex processes produce mutations (errors, residue). (halting problem)
  9. 9. Data As Marks in a substrate. Differences in a medium. Transmittable Marks. The pages of words and music and math symbols are just ordered marks. They are data in a huge number of different ways.  Linear codex of left to right English writing  Musical Notation  Mathematical Symbols  Music and Math Theories  The words definitions  … A detector needs context/previous exposure to this data as well as use of the data through other detectors to understand/interpret this data. (play music on a musical instrument...)
  10. 10. Data As Maps. (Projective Geometry) Data maps mediums between mediums. The world’s resources are controlled by projection maps. High dimensional data (complex real world stuff) requires topological approaches for any sense.
  11. 11. Data Becomes Through Experimentation. Data isn’t data until something happens.... Emmer wheat… mutated into big seeds that found reasonable ground… got noticed by some Neolithic folks… and then civilization happened. Gravitational waves aren’t data until something really big happens, like a couple of blackholes getting together. … and there’s a detector to detect it.
  12. 12. Data is: About Others and Itself Of Relations Relates Others To Others Becomes Through Experiment Learning is Noticing and Experimenting with Difference. (What was that glitch? Is that glitch a glitch in other mediums?) Data Science is Experimentation Simulation Art Transmitting Phenomena From One Medium to Another and testing to see what maintains coherence, meaning, use. Data that is really data is ROBUST through media.
  13. 13. Art is The Future of Data Science (always has been) Art is about making something happen. Noticing what’s noticed. Recursing noticing & happening. 1203 painting s 2 art shows 13 hrs of video 155 sale s +38% single day revenue increase for show locations 14,000,000 + marks Analyze all my marks. Analyze all show behavior
  14. 14. Do people want to learn about the Self or the Truth? But! Truth had pull! 90% of humans are right handed/footed (ants are left first biased too!). 73%73%73% 27%
  15. 15. All Businesses Are Art Business as Art As Data Science If a business produces something robust, it will transmit across mediums. And this exercise is getting really complicated.
  16. 16. It really is about noticing... … the ever changing relationships between things.
  17. 17. Another Surprising Example of Noticing ...a new product in video/tv content is to ACCELERATE the viewing speed.
  18. 18. Dilemma. How do you QA and do data in an infinite virtual world? How do you QA and ensure safety in infinite live video? “What might just happen is the proliferation of archi-tectural clones around the globe, of transparent, interactive, mobile, fun buildings modeled on networks and virtual realities—by which a whole society basically gives itself the comedy of culture, the comedy of communication, the comedy of the virtual (just as it gives itself the comedy of politics, for that matter). “ Architecture: Truth or Radicalism? by Jean Baudrillard
  19. 19. Data Science is Simulation is Art. We will assess CONSEQUENCES through integrated simulations of new relationships deployed in virtual reality with complex adaptive avatars. • Unsupervised learning driven avatars in virtual universes trying out our ideas • Instigating and Tracking behavior… “Virtual Skinner Boxes” • Assessments of Acceptable Risk Networks lead to adoption and integration of policy/tech/software from the virtual to the real
  20. 20. Insight from noticing what’s noticed. We make data detectors. We detect data. We publish data to be detected.
  21. 21. Hadoop is essential. Hadoop (the ecosystem) remains the most generalized collection of data detectors.
  22. 22. Machine Learners SOME EXPERIENCE
  23. 23. Thank You Business: Displeasure: @un1crom (on instagram and twitter) Criticism: