Successfully reported this slideshow.
Your SlideShare is downloading. ×

Using data visualization for accessible science (communication)

Ad
Ad
Ad
Ad
Ad
Ad
Ad
Ad
Ad
Ad
Ad

Check these out next

1 of 113 Ad

Using data visualization for accessible science (communication)

Download to read offline

23 November 2022…
GFDL Lunchtime Seminar Series

Creating visualizations of complex data structures and patterns is an important part of our jobs. We use figures for journal publications, presentations, posters, lab group meetings, science communication, and more. However, creating suitable figures for the task can sometimes be an afterthought during the extensive scientific process. In this seminar, I’ll share examples from climate science to discuss a network of resources available for designing accessible figures in both publications and presentations by leveraging resources that support open science practices. I will also share examples of what not to do, which goes beyond only considering interpretable colormaps, and how to improve these figures moving forward. Finally, by using global mean surface temperature as a case study, I will share some creative instances of using data visualization as a form of storytelling for communicating climate change.

23 November 2022…
GFDL Lunchtime Seminar Series

Creating visualizations of complex data structures and patterns is an important part of our jobs. We use figures for journal publications, presentations, posters, lab group meetings, science communication, and more. However, creating suitable figures for the task can sometimes be an afterthought during the extensive scientific process. In this seminar, I’ll share examples from climate science to discuss a network of resources available for designing accessible figures in both publications and presentations by leveraging resources that support open science practices. I will also share examples of what not to do, which goes beyond only considering interpretable colormaps, and how to improve these figures moving forward. Finally, by using global mean surface temperature as a case study, I will share some creative instances of using data visualization as a form of storytelling for communicating climate change.

Advertisement
Advertisement

More Related Content

More from Zachary Labe (20)

Recently uploaded (20)

Advertisement

Using data visualization for accessible science (communication)

  1. 1. USING DATA VISUALIZATION FOR ACCESSIBLE SCIENCE (COMMUNICATION) Zachary Labe Postdoc in Seasonal-to-Decadal (S2D) Variability and Predictability Division zachary.labe@noaa.gov GFL – 23 November 2022 – Lunchtime Seminar @ZLabe https://zacklabe.com/arctic-sea-ice-figures/ 🌐
  2. 2. The Arctic is warming more than 3 times faster than the global average!
  3. 3. NOW Start of satellite-era
  4. 4. DATA VISUALIZATION IS STORY-TELLING. Arctic temperature anomalies from 1950 to 2021
  5. 5. DON’T BE SUCH A SCIENTIST WE ARE DATA SCIENTISTS ART BY JILL PELTO
  6. 6. Landscape of Change uses data about sea level rise, glacier volume decline, increasing global temperatures, and the increasing use of fossil fuels. These data lines compose a landscape shaped by the changing climate, a world in which we are now living. Jill Pelto|https://www.jillpelto.com/landscape-of-change “ ”
  7. 7. WHAT ARE YOUR WORST FIGURES?
  8. 8. My first map subplot?
  9. 9. LABE ET AL. 2017, CLIMATE DYNAMICS
  10. 10. Arctic sea ice thickness variability and the atmospheric circulation Zachary M. Labe Gudrun Magnusdottir 2 June 2016
  11. 11. BEGINNING WITH OUR DATA.
  12. 12. LINE GRAPHS Temperature Anomaly (°C)
  13. 13. :)
  14. 14. MAP PLOTS
  15. 15. YIKES!
  16. 16. YIKES – FONT IS BLEH!
  17. 17. YIKES – COLOR!
  18. 18. MAP PROJECTION!
  19. 19. :)
  20. 20. HAVE FUN!
  21. 21. LEVERAGING ALL DIMENSIONS OF YOUR DATA.
  22. 22. I have a 2D-array of sea ice thickness anomaly data [year,day]… Each line is one day Number of Years Thickness Anomaly (m)
  23. 23. https://seaborn.pydata.org/examples/index.html
  24. 24. https://betterfigures.org/2012/09/15/decadal-temperatures/ Error bars and graphical clutter…
  25. 25. https://betterfigures.org/2012/09/15/decadal-temperatures/ Error bars and graphical clutter…
  26. 26. https://betterfigures.org/2012/09/15/decadal-temperatures/ Error bars and graphical clutter…
  27. 27. SURPRISINGLY EFFECTIVE.
  28. 28. DANISH METEOROLOGICAL INSTITUTE
  29. 29. SCIENCE OF DESIGN.
  30. 30. cmap = ‘jet’
  31. 31. STOELZLE AND STEIN, 2021, HESS
  32. 32. 1998!
  33. 33. Citations on Google Scholar…
  34. 34. Check out: https://betterfigures.org/2018/06/04/playing-hunt-the-discontinuity/
  35. 35. 2004!
  36. 36. WESTAWAY, 2022, GC
  37. 37. WESTAWAY, 2022, GC
  38. 38. SCHNEIDER AND NOCKE, 2017
  39. 39. SCHNEIDER AND NOCKE, 2017
  40. 40. SCHNEIDER AND NOCKE, 2017
  41. 41. SCHNEIDER AND NOCKE, 2017
  42. 42. SCHNEIDER AND NOCKE, 2017
  43. 43. Crameri, F. (2018). Scientific colour maps. Zenodo. http://doi.org/10.5281/zenodo.1243862 Crameri, F. (2018), Geodynamic diagnostics, scientific visualisation and StagLab 3.0, Geosci. Model Dev., 11, 2541- 2562, doi:1 0.5194/gmd-11-2541-2018 Crameri, F., G.E. Shephard, and P.J. Heron (2020), The misuse of colour in science communication, Nature Communications, 11, 5444. doi:10.1038/s41467-020-19160-7
  44. 44. BY FABIO CRAMERI
  45. 45. BY FABIO CRAMERI
  46. 46. Crameri, F. (2018). Scientific colour maps. Zenodo. http://doi.org/10.5281/zenodo.1243862 Crameri, F. (2018), Geodynamic diagnostics, scientific visualisation and StagLab 3.0, Geosci. Model Dev., 11, 2541- 2562, doi:1 0.5194/gmd-11-2541-2018 Crameri, F., G.E. Shephard, and P.J. Heron (2020), The misuse of colour in science communication, Nature Communications, 11, 5444. doi:10.1038/s41467-020-19160-7 Palettable: Color palettes for Python
  47. 47. PALETTABLE - PYTHON
  48. 48. TURBO https://ai.googleblog.com/2019/08/turbo-improved-rainbow-colormap-for.html
  49. 49. OTHER OPTIONS THYNG ET AL. 2016; OCEANOGRAPHY
  50. 50. CMOCEAN THYNG ET AL. 2016; OCEANOGRAPHY
  51. 51. CMASHER “Scientific colormaps for making accessible, informative and cmashing plots”
  52. 52. Adapted from Ed Hawkins at betterfigures.org
  53. 53. Adjusting axes (spines)
  54. 54. Changing font styles
  55. 55. 1. Seaborn. 2. Plotly. 3. ggplot. 4. Matplotlib v3. RESOURCES
  56. 56. 1. https://betterfigures.org/ 2. https://www.climate-lab-book.ac.uk/ 3. http://colorbrewer2.org/ RESOURCES
  57. 57. LABE ET AL. 2019, GRL Bring drama to your data story
  58. 58. LABE ET AL. 2019, GRL
  59. 59. LABE ET AL. 2019, GRL STRONGER POLAR VORTEX Zonal wind at 10 hPa Geopotential at 30 hPa
  60. 60. WEAKER POLAR VORTEX Zonal wind at 10 hPa Geopotential at 30 hPa LABE ET AL. 2019, GRL
  61. 61. 2-m TEMPERATURE Future minus Pre-Industrial PEINGS, LABE ET AL. 2021, JCLI
  62. 62. 2-m TEMPERATURE Future minus Pre-Industrial PEINGS, LABE ET AL. 2021, JCLI
  63. 63. 2-m TEMPERATURE Future minus Pre-Industrial PEINGS, LABE ET AL. 2021, JCLI
  64. 64. 2-m TEMPERATURE Future minus Pre-Industrial PEINGS, LABE ET AL. 2021, JCLI
  65. 65. 2-m TEMPERATURE Future minus Pre-Industrial PEINGS, LABE ET AL. 2021, JCLI
  66. 66. 2-m TEMPERATURE Future minus Pre-Industrial PEINGS, LABE ET AL. 2021, JCLI
  67. 67. 2-m TEMPERATURE Future minus Pre-Industrial PEINGS, LABE ET AL. 2021, JCLI
  68. 68. Perceiving internal climate variability WITT, LABE ET AL. 2022; submitted
  69. 69. MAKING ACCESSIBLE FIGURES.
  70. 70. ACCESSIBILITY
  71. 71. ACCESSIBILITY
  72. 72. ACCESSIBILITY
  73. 73. ACCESSIBILITY No jargon Tell a story Alternative text Color contrast ratio Label data directly Avoid flashing GIFs Include figure titles Avoid data overlays Provide data references
  74. 74. VISUALIZING GLOBAL TEMPERATURE CHANGE
  75. 75. 2016 RIO OLYMPICS OPENING CEREMONY
  76. 76. PLOT BY ED HAWKINS
  77. 77. PLOT BY ED HAWKINS DON’T BE SUCH A SCIENTIST WE ARE DATA SCIENTISTS
  78. 78. https://showyourstripes.info/
  79. 79. CHECK: Simple. Bold. Stories. @ZLabe Questions! https://zacklabe.com/arctic-sea-ice-figures/ ZACHARY LABE | 23 NOVEMBER 22| GFDL LUNCHTIME SEMINAR

×