GIScience and CyberGIS

1. GIScience and CyberGIS Michael F. Goodchild University of California Santa Barbara

2. The vision of CI-supported science • Teams studying complex questions • distributed across disciplines • with disparate practices • distributed geographically • with powerful communication links • perhaps distributed temporally as well • Access to vast repositories of data • possibly real-time • using powerful search tools • with comprehensive documentation • metadata, provenance, etc.

3. More on the vision • Access to powerful software tools • manipulation, analysis, modeling • interoperable • easy to match to data • Powerful computation • supercomputers • Well-connected communities • skilled in the use of CI • easy recruitment, team formation • Efficient methods of knowledge sharing

4. What’s special about spatial? • Vision is generic • is there a specifically spatial perspective? • a specific case for cyberGIS? • In some ways GIS is already ahead of the field • National Spatial Data Infrastructure 1993 • metadata since 1992 • geolibraries since 1993, geoportals • OGC standards (WMS, etc.) • a tradition of data sharing • much in the public domain, Feist, etc.

5. Community engagement • GIS functions available to all • People love maps • VGI • But in the scientific community • generalizing away from space and time • variable takeup of GIS • a belief that it is intuitively obvious • no widely recognized theory or principles • reluctance to see GIS as comparable to e.g. statistics

6. Elements of a geospatial CI • Base mapping • easy-to-use mapping tools • Google Maps API, ArcGIS Online • boundary files • Gazetteers, point-of-interest databases • geonames.org, Google Maps API, etc. • interoperability of georeferencing styles • Geocoding services • Powerful analysis packages • GeoDa, ArcGIS, R, Matlab, etc.

7. maps.google.com

8. raconline.org

9. www.csiss.org

10. More elements • Geodemographics • Census data mapping • PRIZM, Tapestry, etc. • National Spatial Data Infrastructure • 7 base layers

11. So why the interest in cyberGIS? • Speedup? • how much effort is a speedup worth? • Scale • being able to perform simulations and develop models on n = 106+ elements • making scale explicit • and addressing the MAUP and ecological fallacy

12. Because we can avoid shortcuts • No need for Pythagorean distances • all analysis on a curved Earth • new methods needed • No need to divide and conquer • small study areas • difficult to generalize from • No need to restrict to least squares • use nonlinear optimization • No need for parametric inferential statistics • use simulation and randomization tests

13. More reasons for interest • Because the Earth’s systems really are parallel • humans and communities are semi-independent agents making simultaneous decisions • but conventional computing is serial • the architecture of cyberGIS can be closer to the architecture of the real world’s processes • Because today’s science problems really are more complex • requiring multidisciplinary, distributed teams

14. New kinds of data • Big Data • Closer to real-time • Vastly increased volume • Poor and diminishing quality control • from disparate sources • no lengthy synthesis by experts • no metadata or provenance • Need to automate quality control • and the production of metadata and provenance

15. The characteristics of Big Data • Volume • peta-, exabyte scale • zetta (1021) • yotta (1024) • the mass of the Earth is 5,973.6 Yg • Velocity • rapid change, speed of analysis • Variety • many sources • varied quality

16. New kinds of analysis • Of data with unknown or variable quality • More suited to hypothesis generation than hypothesis testing • the softer end of science • exploration, sampling design • induction • An increased role for machine learning

17. Challenging the norms of science • Collective responsibility • plagiarism • The black box • impossible to know all details of a project • Replicability • impossible to report in sufficient detail • Experimental design • Poor data • and therefore poor results

18. New concepts of knowledge • David Weinberger, Too Big to Know • A strong legacy • academic advancement • No stop events • publication • All knowledge is contested • All knowledge is uncertain

19. Selling the vision • Why is cyberGIS important? • because it enables new applications, new discoveries • possibilities that were not realized before • Has the case been made? • or is this a matter of faith? • We need a set of compelling examples • of what could not be done without cyberGIS

21. Accessibility • CyberGIS must be more accessible than GIS • to a larger user community • advanced technology tends to move initially in the opposite direction • only then will users be motivated to adopt • Shorter learning curve • More intuitive user interfaces • Interoperable across more knowledge communities • How accessible is GIS?

22. The user interface problem • To support CyberGIS, service-oriented architectures, discovery of services, interdisciplinary research • we must formalize functionality • a common language to describe operations • interoperability across functions • a radically different user interface • In 40 years of GIS development this has not been achieved • functionality is ad hoc, legacy, artifactual

24. Questions users want to ask • To answer Question A you need to use Function B • or Function B1 followed by Function B2 followed by Function B3…

26. The Andy Mitchell books • Mitchell A. The ESRI guide to GIS analysis. I. Geographic patterns and relationships. Redlands, CA: ESRI Press; 1995. • Mitchell A. The ESRI guide to GIS analysis. II. Spatial measurements and statistics. Redlands, CA: ESRI Press; 2005. • Mitchell A. The ESRI guide to GIS analysis. III. Modeling suitability, movement, and interaction. Redlands, CA: ESRI Press; 2012.

27. Topics of Volume I • Mapping Where Things Are • Mapping the Most and Least • Mapping Density • Finding What’s Inside • Finding What’s Nearby • Mapping Change

28. If you had an infinite supply of computing power how would you deploy it? • On bigger simulation models? • On synthesizing and analyzing larger quantities of data? • On tools to allow researchers to collaborate better? • On making the user interface more accessible?

29. Meet Dr Geo Analytics • Ask Geo • Where are the counties with the highest percent uninsured? • Do these tend to be rural counties? • How is x related to y? • when x and y have different spatial support?

30. Towards a successful CyberGIS • Think like a user • as well as a technically expert GIScientist • Understand why CyberGIS is important • and how to argue that • to an anthropologist or an ecologist • in 30 seconds • Simplify • the product must be easy to learn and use • as well as powerful and scientifically rigorous • Think ahead • today’s technologies will evolve

31. CyberGIS as a game-changer • Rethinking many aspects of GIS • Changing traditional practices • Asking new questions • be willing to move beyond the old questions • Galileo’s telescope allowed him to ask new questions • Creating new priorities • A powerful vision • and a wealth of opportunity