1. Linked Micromaps: Statistical Summaries of Monitoring Data in a Spatial Context Michael G.McManus 1, Quinn Payton 2, Marc H. Weber 3, Thomas M. Kincaid 3, Anthony R. Olsen 3 1 Office of Research and Development National Center for Environmental Assessment, Cincinnati, OH 2 Department of Statistics, Oregon State University 44 Kidder Hall Corvallis, OR Corvallis, OR 3 Office of Research and Development National Health and Environmental Effects Research Lab, Corvallis, OR The views expressed in this presentation are those of the authors and do not necessarily reflect the views and polices of the U.S. Environmental Protection Agency. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.

2. The “…goal of a map is to stimulate a hypothesis…” Alan MacEachren, How Maps Work 2

3. Linked Micromap Definition A graphic that simultaneously summarizes and displays both statistical and geographic distributions by linking statistical summaries to a series of small maps 3

4. Outline I. Maps and Statistical Summaries II. Elements of a Linked Micromap III. Linked Micromaps of Aquatic Surveys IV. Steps to Make a Linked Micromap V. Challenges & Conclusions 4

5. I. Three Options: National Lake Assessment pH 1. Pin Map 2. Choropleth Map 3. Linked Micromap 5

6. 6 Pin Map

7. Choropleth Map 7

8. Linked Micromap: Insight & Implementation Separate the statistical data from the spatial data, but still keep them linked via a color-coded legend Sort the data based on a summary statistic, group it into small chunks, and make a series of small maps or map caricatures 8

9. 9 Modified from Symanzik, J. and Carr, D. B. 2008. Interactive Linked Micromap Plots for the Display of Geographically Referenced Statistical Data. In, Handbook of Data Visualization. Chen, Chun-houh; Härdle, Wolfgang;Unwin, Anthony (Eds.). Springer. Panels Perceptual Groups II. Elements of a Linked Micromap

10. III. NLA Linked Micromap 10

11. III. Benefits of Linked Micromaps Apply to shapefile of areal units (watersheds, ecoregions, etc.) Display measures of variation (IQR, CL) Facilitate exploratory spatial data analysis (local, global outliers) Compare statistical summaries to a reference value Evaluate multiple variables simultaneously 11

12. III. Example Stream Conductivity 12

13. III. ESDA 13

14. III. Example of Reference Line 14

15. IV. Four Steps to Make a Linked Micromap A. Geoprocessing of Spatial Data, or Polygons, in GIS or R B. Structuring the Spatial and Statistical Data C. Making the Draft Linked Micromap Plot D. Refining the Linked Micromap Plot 15

16. V. Challenges of Linked Micromaps Displaying summaries of many areal units Add other types of graphs for statistical summaries Make interactive for web applications 16

17. V. Conclusion Linked micromaps can be used to visualize georeferenced monitoring data in a way to stimulate hypotheses. 17

18. V. Outreach & Conclusions Journal of Statistical Software article special issue on spatial statistics Dr. Sala Senkayi, EPA Region 6, applying to public health data Webinars to agency scientists & in-person workshop at 9 th National Monitoring Conference in Cincinnati so micromaps can be used in Integrated Water Quality Monitoring and Assessment reports Dr. Juergen Symanzik using in Applied Spatial Statistics course at Utah State University 18

19. V. Applications & Conclusions Peterson, G. (February 28, 2011). Micromap Software. Blog by Gretchen Peterson.Blog by Gretchen Peterson Robbins, N. (May 23, 2012). Linked Micromaps for Geographically Referenced Data. Blog by Naomi Robbins.Blog by Naomi Robbins Zhang, C. (2012). Interfaces and Visual Analytics for Visualizing Spatio- Temporal Data with Micromaps Symanzik, J. and Carr, D.B. (2013) Linked Micromap Plots in R. Proceedings of Joint Meeting of the IASC Satellite Conference and the 8 th Conference of the Asian Regional Section of the IASC. Theme: Big Data and Statistical Computing. http://hbutton.com/IASC/http://hbutton.com/IASC/ 19

20. Contact Information For questions and suggestions about the library please email us:  Mike McManus – mcmanus.michael@epa.govmcmanus.michael@epa.gov  Marc Weber – weber.marc@epa.govweber.marc@epa.gov  Quinn Payton – paytonq@science.oregonstate.edupaytonq@science.oregonstate.edu 20

21. Acknowledgements Examples of code from Dan Carr at George Mason University, Jüergen Symanzik, and Samson Gebread, both at Utah State University, were very helpful. Brian Diggs at Oregon Health and Science University provided an example of linked micromap coding using ggplot2. Thanks to Jeffrey Bailey, Michael Whitman, and John Wirts of West Virginia Department of Environmental Protection for providing data. 21