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Data visualisation

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Data visualisation

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The following resource was developed by RESYST for a research uptake workshop held in Kilifi, Kenya.

In this resource:
- Introduce data visualisation and demonstrate its value for research uptake and communications
- Compare different types of chart
- Share design tips for a visualisation
- Explore online data visualisation tools

Find more: http://resyst.lshtm.ac.uk/resources/resource-bank-research-uptake

The following resource was developed by RESYST for a research uptake workshop held in Kilifi, Kenya.

In this resource:
- Introduce data visualisation and demonstrate its value for research uptake and communications
- Compare different types of chart
- Share design tips for a visualisation
- Explore online data visualisation tools

Find more: http://resyst.lshtm.ac.uk/resources/resource-bank-research-uptake

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Data visualisation

  1. 1. Data visualisation Research uptake workshop 12-14 September 2017 Kilifi, Kenya http://resyst.lshtm.ac.uk @RESYSTresearch
  2. 2. In this resource • Introduce data visualisation and demonstrate its value for research uptake and communications • Compare different types of chart • Share design tips for a visualisation • Explore online data visualisation tools
  3. 3. • The presentation of data or information in a graphical format • A way of visually communicating information – often quantitative in nature – in an accurate, compelling way What is data visualisation?
  4. 4. http://www.nytimes.com/interactive/2012/11/24/opinion/sunday/what-could-disappear.html
  5. 5. The value of data visualisations • Reveal patterns, relationships or stories in data • Tell stories in a compelling and immediate way which can be more memorable than words or tables Life expectancy at birth 19 80 19 82 19 84 19 86 19 88 19 90 19 92 19 94 19 96 19 98 20 00 20 02 20 04 20 06 20 08 20 10 20 12 Botswana 61 62 63 63 64 63 62 59 56 53 51 49 47 47 46 47 47 India 55 56 57 57 58 59 59 60 61 61 62 63 64 64 65 66 66 South Africa 57 58 59 60 61 62 62 62 61 58 56 54 52 52 53 55 56 Tanzania 51 51 51 51 51 50 50 49 49 49 50 51 53 55 57 59 61 Zimbabwe 59 60 61 61 61 59 57 53 50 46 44 43 43 45 49 54 58
  6. 6. The value of data visualisations • Visualisations can be easily shared with others
  7. 7. The value of data visualisations • Effective visualisations can alter perceptions, influence people and bring about change
  8. 8. Column/bar charts Pros • Clear and easy to read • Show even small differences in values Cons • Can be dull • People rarely stop and look Source: The Guardian http://www.theguardian.com/society/2013/jun/20/one-in-three-women-suffers-violence
  9. 9. Pie charts Pros • Pie charts are good for showing percentages. Cons • Don’t represent values accurately, which makes it hard to compare values.
  10. 10. Pie charts
  11. 11. Stacked bars Pros • Good alternative to pie charts when you have values adding up to 100% Cons • Can be hard to compare values in the middle. • Lose smaller values
  12. 12. Bubble charts
  13. 13. Bubble charts: optical illusions
  14. 14. Design tips • Represent the data accurately • Style the chart simply • Use colour with caution • Choose a clear font • Use annotations to tell a story
  15. 15. Represent the data accurately Always scale to zero
  16. 16. Represent the data accurately Don’t use 3D charts
  17. 17. Represent the data accurately Circle size by area, not radius Size by radius Size by area 1 2 4
  18. 18. Represent the data accurately Provide context
  19. 19. Style the chart simply Use a limited colour palette
  20. 20. Style the chart simply Don’t fill with patterns
  21. 21. Style the chart simply Mute gridlines
  22. 22. Style the chart simply Order by value
  23. 23. Style the chart simply Label as directly as possible Series 1 Series 2 Series 3 0 1 2 3 4 5 6 1990 1995 2000 2005 0 1 2 3 4 5 6 1990 1995 2000 2005 Series 1 Series 2 Series 3
  24. 24. Use colour with caution monochromatic complementary Analogous (similar)
  25. 25. Use colour with caution 0 5 10 15 20 Monochromatic colours for a data map Complementary colours to highlight Similar colours to distinguish data Bright colours to emphasise the important line
  26. 26. Use colour with caution Have consideration for the meaning of colours What is wrong with this picture?
  27. 27. Use colour with caution Don’t use red and green together
  28. 28. Choose a clear font For screen • Calibri • Helvetica • Franklin Gothic • Arial For print • Georgia • Garamond • Baskerville • Times New Roman
  29. 29. 4. Choose a clear font Is this easy to read? Is this easy to read? Is this easy to read? Is this easy to read? IS THIS EASY TO READ? Is this easy to read?
  30. 30. Use annotations to tell a story Highlight important features Provide additional detail, context
  31. 31. Online tools: infogram https://infogram.com
  32. 32. Organise your information Find data Clean data • Research, WHO data, World Bank data • In excel, check data is accurate, re-format Remove commas, irrelevant data Decrease decimals Switch rows to columns (Copy -- Paste Special -- Transpose Sort data • Into separate spreadsheets for each graphic
  33. 33. Further resources for data visualisation • STRIVE/RESYST webinar on data visualisation • Infogram • Tableau public • The noun project • Knowledge is beautiful – book and website by David McCandless • The visual display of qualitative information book
  34. 34. This resource was produced by Becky Wolfe © RESYST 2017 and licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported License. Becky Wolfe is a member of the Consortium for Resilient and Responsive Health Systems (RESYST). This document is an output from a project funded by the UK Aid from the UK Department for International Development (DFID) for the benefit of developing countries. However, the views expressed and information contained in it are not necessarily those of or endorsed by DFID, which can accept no responsibility for such views or information or for any reliance placed on them.

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