1. Visualisation 2012 - 2013 Lecture 3 Brian Mac Namee Dublin institute of Technology Applied Intelligence Research Centre Visualising Trends

2. Origins This course is based heavily on a course developed by Colman McMahon (www.colmanmcmahon.com)www.colmanmcmahon.com Material from multiple other online and published sources is also used and when this is the case full citations will be given 2 2011/12

3. Visualization of the Week www.pinterest.com/brianmacnamee/great-visualisation-examples/

4. (Un)Visualization of the Week www.pinterest.com/brianmacnamee/terrible-visualisation-examples/

5. Agenda Visualising patterns over time Discrete points in time Continuous points in time Handling multiple dimensions over time 5 2011/12

6. What To Look For The most common thing you look for in time series, or temporal, data is trends - Is something increasing or decreasing? - Are there seasonal cycles? To find these patterns, you have to look beyond individual data points to get the whole picture

7. 2011/12 7

8. Visualising Patterns Over Time Visualising patterns over time - Discrete points in time Bar Graph Scatter Plot - Continuous points in time Line Chart Step Chart - Handling multiple dimensions over time Stacked Bar Chart Area Chart Stream Graph Small Multiples Animation 2011/12 8

9. Discrete Points In Time Often we have datasets that contain single measurements for a reasonably small number of discrete points in time - Profit per year - Rainfall per month In these cases a simple bar graph is often appropriate

10. Simple Bar Graph “Visualize This”, N. Tau, Wiley, 2011 http://shop.oreilly.com/product/0636920022060.do

11. Simple Bar Graph “Visualize This”, N. Tau, Wiley, 2011 http://shop.oreilly.com/product/0636920022060.do

12. Simple Bar Graph http://www.mornpen.vic.gov.au/page/imageThumbnail.asp?C_Id=820

13. Continuous Points In Time Often we have datasets that contain single measurements for a number of continuous points of time - Stock prices over time - Internet traffic over time In these cases a line charts are more appropriate

14. Simple Scatter Plot 2011/12 14 “Visualize This”, N. Tau, Wiley, 2011 http://shop.oreilly.com/product/0636920022060.do

15. Simple Scatter Plot “Visualize This”, N. Tau, Wiley, 2011 http://shop.oreilly.com/product/0636920022060.do

16. Simple Line Chart Simply adding a line to a scatter plot can help greater emphasise a trend over time “Visualize This”, N. Tau, Wiley, 2011 http://shop.oreilly.com/product/0636920022060.do

17. Simple Line Chart “Visualize This”, N. Tau, Wiley, 2011 http://shop.oreilly.com/product/0636920022060.do

18. Simple Line Chart “Visualize This”, N. Tau, Wiley, 2011 http://shop.oreilly.com/product/0636920022060.do

19. Step Chart Basic line charts interpolate the change in measurement from one point in time to another Often this is not appropriate and in these cases step charts are more appropriate “Visualize This”, N. Tau, Wiley, 2011 http://shop.oreilly.com/product/0636920022060.do

20. Step Chart 2011/12 20 “Visualize This”, N. Tau, Wiley, 2011 http://shop.oreilly.com/product/0636920022060.do

21. Step Chart “Visualize This”, N. Tau, Wiley, 2011 http://shop.oreilly.com/product/0636920022060.do

22. Fitting A Line In some cases adding a line to a scatter plot can mask the trend over time rather than help illustrate it In this cases it can be more appropriate to fit a line or curve to a dataset so as to highlight a trend in time ACHTUNG: Be careful when fitting lines, it is possible to illustrate trends that don’t really exist

23. Fitting A Line “Visualize This”, N. Tau, Wiley, 2011 http://shop.oreilly.com/product/0636920022060.do

24. Smoothing & Estimation 2011/12 24 “Visualize This”, N. Tau, Wiley, 2011 http://shop.oreilly.com/product/0636920022060.do

25. Multiple Dimensions In Time Often we have datasets that contain multiple measurement for each point in time which gives us multiple dimensions This makes visualization more challenging as we need to use newer and different encodings There are a number of approaches we can take

26. Stacked Bar Chart “Visualize This”, N. Tau, Wiley, 2011 http://shop.oreilly.com/product/0636920022060.do

27. Stacked Bar Chart Charting U.S. Gun Manufacturing, Matt Stiles, The Daily Viz, 2012 http://thedailyviz.com/2012/08/07/charting-u-s-gun-manufacturing/

28. Stacked Bar Chart Interpreting multiple time series in a stacked bar chart can be really difficult, especially when we need to interpret the trend within the higher categories Only really appropriate when the real trend we want to illustrate is the overall total bar height trend and the individual categories are secondary

29. Multiple Line Series http://hci.stanford.edu/jheer/files/zoo/ex/time/index-chart.html

30. Multiple Line Series Displaying time-series data: Stacked bars, area charts or lines…you decide!, VizWiz, 2012 http://vizwiz.blogspot.ie/2012/08/displaying-time-series-data-stacked.html U.S. Gun Manufacturing By Type

31. Stacked Area Chart “Visualize This”, N. Tau, Wiley, 2011 http://shop.oreilly.com/product/0636920022060.do

32. Stacked Area Chart U.S. Gun Manufacturing By Type Displaying time-series data: Stacked bars, area charts or lines…you decide!, VizWiz, 2012 http://vizwiz.blogspot.ie/2012/08/displaying-time-series-data-stacked.html

33. Stacked Area Chart Stacked area charts unfortunately suffer from many of the same problems as stacked bar charts It can be very hard to interpret the trends of each category as they are stacked on top of each other

34. Stacked Area Chart Displaying time-series data: Stacked bars, area charts or lines…you decide!, VizWiz, 2012 http://vizwiz.blogspot.ie/2012/08/displaying-time-series-data-stacked.html What does the shotgun trend look like?

35. Stacked Area Chart Displaying time-series data: Stacked bars, area charts or lines…you decide!, VizWiz, 2012 http://vizwiz.blogspot.ie/2012/08/displaying-time-series-data-stacked.html

36. Stream Graph The Stream Graph is an attempt to overcome the difficulties associated with stacked bar charts and stacked area charts

37. Stream Graph ThemeRiver: Visualizing Theme Changes over Time, Susan Havre, Beth Hetzler, Lucy Nowell, Proc. IEEE Symposium on Information Visualization, 2000. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.135.4974 http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.135.4974

38. Stream Graph ThemeRiver: Visualizing Theme Changes over Time, Susan Havre, Beth Hetzler, Lucy Nowell, Proc. IEEE Symposium on Information Visualization, 2000. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.135.4974 http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.135.4974

39. Stream Graph Stacked Graphs – Geometry & Aesthetics, Lee Byron & Martin Wattenberg, 2008. http://www.leebyron.com/what/lastfm/ http://www.leebyron.com/what/lastfm/

40. Stream Graph Stacked Graphs – Geometry & Aesthetics, Lee Byron & Martin Wattenberg, 2008. http://www.leebyron.com/what/lastfm/ http://www.leebyron.com/what/lastfm/

41. Stream Graph Stacked Graphs – Geometry & Aesthetics, Lee Byron & Martin Wattenberg, 2008. http://www.leebyron.com/what/lastfm/ http://www.leebyron.com/what/lastfm/

42. Stream Graph http://hci.stanford.edu/jheer/files/zoo/ex/time/stack.html

43. The Ebb and Flow of Movies: Box Office Receipts 1986 — 2008, New York Times http://www.nytimes.com/interactive/2008/02/23/movies/20080223_REVENUE_GRAPHIC.html http://www.nytimes.com/interactive/2008/02/23/movies/20080223_REVENUE_GRAPHIC.html Stream Graph

44. Small Multiples One solution to illustrating time is to use small multiples to show multiple snapshots of the data at different points in time

45. Small Multiples http://hci.stanford.edu/jheer/files/zoo/ex/time/multiples.html

46. Small Multiples

47. Tres Epistolae de Maculis Solaribus Scriptae ad Marcum Welserum, Christoph Scheiner, 1612 http://galileo.rice.edu/sci/observations/sunspots.html

48. Animation Animation is obviously a great way to illustrate changes over time We will look at this more later in the course

49. Animation www.ted.com/talks/hans_rosling_shows_the_best_stats_you_ve_ever_seen.html

50. Animation Galileo's Sunspot Drawings http://galileo.rice.edu/sci/observations/ssm_slow.mpg http://galileo.rice.edu/sci/observations/ssm_slow.mpg Gallileo made flip books of sunspot images to show how they moved over time

51. Conclusions Visualising across time is a key methodology There are a number of approaches that are common and useful We will come back to animation