This document discusses how data visualization can make data science more tangible and accessible. It provides examples of using maps and interactive visualization to tell stories with data and simplify complex datasets. Visualization tools can turn raw data into insights by aggregating information over space and time. The document advocates using all dimensions of data, like integrating 3D models with spatiotemporal data, to better understand assets and dynamic systems.

1. Making Data Science Tangible
Gregory Brunner, Esri
Data Pop-up Chicago
November 14, 2017

2. I usually talk about Python or image science
But I’m really excited about data visualization!

3. Geoviz can make data science tangible

4. “Is cartography becoming data science?”
Discussion between @cerebellumaps,
@jwasilgeo,
and me

5. Canvas flow map – Data science or data visualization?
https://github.com/sarahbellum/Canvas-Flowmap-Layer

6. Vector Tiles – Data science or data visualization?
https://github.com/maplabs/mapstyler

7. Rendering billions of points – Data science or data visualization? Or both?

8. What we do and how we do it is changing
1970’s 2017

9. “Data visualization has the potential to
make data science more tangible.”
Sarah Bell, @cerebellumaps

10. “Data visualization has the potential to
make data science more tangible.”
will

11. Use it to tell stories

12. Data science needs story
Colleague to me: I don’t need this plot. Can’t you put this data on a map?

13. A few weeks ago in STL
Eric Druker (@SwimDrukes) of BAH talking about The Rise of the Digital Workforce

14. Put this in a map
Mocked up insurance policyholder data

15. Insurance policyholders

16. Total value of insured aggregated into hexbins

17. Policyholders potentially impacted by storm surge

18. We can do more
Turning maps into a story

19. Technology and data aiding in the response to Harvey
https://www.networkworld.com/article/3221334

20. Media for Social Impact
MFSI Summit at UN this past September

21. Technology and data for social impact
https://arcg.is/1XX5Om

22. Use all dimensions

23. The insurance industry has a long history with maps
Sanborn Fire Insurance Maps from the Library of Congress (https://www.loc.gov/)

24. Could this be the modern fire insurance map?
https://github.com/Esri/Manhattan-skyscraper-explorer

25. Index 3D Scene Layers
http://www.opengeospatial.org/standards/i3s
• An Open Standard
• For streaming large volumes of 3D content
• Designed for web, mobile, and cloud
• Works for
- 3D Objects
- Pointclouds
- Meshes

26. Understanding your assets
https://github.com/Esri/c-through

27. Use it to simplify complex data

28. To understand spatio-temporal data
What can you do when you have millions of points over time?

29. Space-time-ripple
https://github.com/mraad/space-time-ripple

30. Dynamic aggregation spatio-temporal data
• What if we want to do this in real-time?
• What if we want to change how the aggregation is rendered?
ArcGIS
Enterprise
GeoEvent
Server
spatiotemporal
big data store
Big DataIoT
GeoAnalytics
Server

31. On-the-fly aggregation
http://coolmaps.esri.com/BigData/Cube/
• Leveraging existing geohash, square, and hexagon aggregation capabilities to
construct space-time bins
• Enables exploration of real-time and historic data
ArcGIS
Enterprise
GeoEvent
Server
spatiotemporal
big data store
Big DataIoT
GeoAnalytics
Server
ArcGIS API for
JavaScript
& WebGL
client-side rendering of
space-time cubes via WebGL

32. Mobile phone aggregations
http://coolmaps.esri.com/BigData/Cube/

33. “Data visualization has the potential to
make data science more tangible.”
will

34. Questions or Feedback?
Gregory Brunner
Senior Scientist, Esri
gbrunner@esri.com
Twitter: @gregbrunn
GitHub: @gbrunner
Blog: www.gavinr.com