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Beyond Academia: Communicating your Work in Academia and Beyond

Career Talk

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Beyond Academia: Communicating your Work in Academia and Beyond

  1. 1. Communicating Your Work in Academia and Beyond William Gunn, Ph.D. Head of Academic Outreach Mendeley twitter: @mrgunn
  2. 2. How many of you currently have working outside of academia as your top choice?
  3. 3. Communicating your work •Content •Medium •Channel •Audience
  4. 4. My story
  5. 5. The advice I got •Good: Pick a stable, well-funded lab where people graduate on time •Good: Diversify project risk •Bad: Keep your head down, work hard, and it’ll all work out
  6. 6. 1.Seek advice from the people who can give it Lessons
  7. 7. The first transition: Grad school to Biotech
  8. 8. I was part of something!
  9. 9. It was a little isolating
  10. 10. 1.Seek advice from the people who can give it 2.Know Thyself Lessons
  11. 11. The second transition: Biotech to tech startup
  12. 12. Early Adopter
  13. 13. ...helps researchers work smarter ...makes science more collaborative and transparent …has created an open research database Tools of scientific discovery Mendeley..
  14. 14. Achievements •OA policy advocacy successes •A tool that doesn’t suck •Altmetrics (Draft NISO standard) •Reproducibility ($1.3M funding and partnership with Center for Open Science)
  15. 15. 1.Seek advice from the people who can give it 2.Know Thyself 3.Look Beyond the Surface Lessons
  16. 16. Stay •What do you want to do? •Will you find "Flow"? •Realistic impression? •Supportive network? •Are you young?
  17. 17. Go •Frustrated by lack of impact? •Like to write? •Want to influence policy? •Are you too charismatic?
  18. 18. Csikszentmihalyi, M. Flow: The psychology of optimal experience. (1991)
  19. 19. MAKING THE TRANSITION Team vs. solo
  20. 20. Communicating your work •Content •Medium – written, spoken, visual •Channel •Audience
  21. 21. Communicating your work •Content •Medium – written, spoken, visual •Channel •Audience
  22. 22. Data viz has a long history John Snow’s cholera map helped communicate the idea that cholera was a water-borne disease.
  23. 23. Florence Nightingale used dataviz
  24. 24. Modernization of dataviz
  25. 25. Chart junk: good, bad, and ugly Which presentation is better?
  26. 26. It can be elegant…
  27. 27. Tufte
  28. 28. Tufte
  29. 29. How our eyes and brain perceive It takes 200 ms to initiate an eye movement, but the red dot can be found in 100 ms or less. This is due to pre-attentive processing.
  30. 30. Shape is a little slower than color!
  31. 31. Pre-attentive processing fails!
  32. 32. There are many “primitive” properties which we perceive •Length •Width •Size •Density •Hue •Color intensity •Depth •3-D orientation
  33. 33. Length
  34. 34. Width
  35. 35. Density
  36. 36. Hue
  37. 37. Color Intensity
  38. 38. Depth
  39. 39. 3D orientation
  40. 40. Types of color schemes •Sequential – suited for ordered data that progress from low to high. Use light colors for low values and dark colors for higher. •Diverging – uses hue to show the breakpoint and intensity to show divergent extremes. •Qualitative – uses different colors to represent different categories. Beware of using hue/saturation to highlight unimportant categories.
  41. 41. Sequential
  42. 42. Diverging
  43. 43. Qualitative
  44. 44. Tips for maps •Keep it to 5-7 data classes •~8% of men are red-green colorblind •Diverging schemes don’t do well when printed or photocopied •Colors will often render differently on different screens, especially low-end LCD screens •
  45. 45. Communicating your work •Content •Medium – written, spoken, visual •Channel •Audience
  46. 46. Adams, Jonathan. "Collaborations: the fourth age of research." Nature 497.7451 (2013): 557-560.
  47. 47. King, Christopher (2012) Thomson Reuters Annual Report
  48. 48. Social Networks Opportunities for discovery Opportunities for building relationships
  49. 49. Scholars on Twitter In a 2010 survey of ~1,400 higher-ed professionals, 1 of 3 used Twitter ( intro
  50. 50. Prevalence of Twitter citations results
  51. 51. Speed (1) If I find an interesting reference in the literature, people will only know about it after one year, maybe, after I have actually published it. However if I tweet it people will know about it immediately, as soon as possible. results - 'Tyrone'
  52. 52. Speed (2) Twitter citations quickly follow article publication: results Priem, J. and Costello, K. L. (2010), How and why scholars cite on Twitter. Proc. Am. Soc. Info. Sci. Tech., 47: 1–4. doi: 10.1002/meet.14504701201
  53. 53. 2.7M researchers
  54. 54.