Data visualisation as a campaign tool for change
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This presentation was for Social Media Week Berlin on Tuesday, 24th September. It was targeted at NGOs, NPOs, activist organisations and charities who have important key messages to share with the community. The event will combine elements of a presentation and workshop. We will examine case studies of campaigns that have successfully used data visualisation in tandem with social media and content marketing techniques to spread information and ideas, and to counteract prevailing myths about climate change and renewable energy technology. We will then allow time for participants to split up into small working groups. Structured discussion tasks and group feedback will allow participants to investigate how these strategies can apply to their own organisation or issue. Participants will learn practical steps for identifying important messages, researching and developing content, incorporating data visualisation in a powerful and meaningful way, and promoting their data visualisation campaigns through social media and email outreach. In particular, the event will focus on developing powerful stories that will attract the support of influential sharers and thought leaders from a range of backgrounds, from activism through to industry, so as to maximise the campaign's reach and impact.
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Data visualisation as a campaign tool for change
- 1. Data Visualisation as a Campaign Tool for Change Presented by for littlewebgiants.com enquiries@littlewebgiants.com Tuesday 24th September, 2013
- 2. What is data visualisation?
- 3. What is data visualisation? Year Number of Pairs 2006 9789 2005 7066 2000 6471 1999 6404 1998 5748 1997 5295 1996 5094 1995 4712 1994 4449 1993 4015 1992 3749 1991 3399 Number of Bald Eagle Breeding Pairs in Lower 48 States Unintelligible information
- 4. What is data visualisation? Number of Bald Eagle Breeding Pairs in Lower 48 States 0 2000 4000 6000 8000 10000 12000 1963 1966 1969 1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005 Intelligible information
- 5. What is data visualisation? The visual representation of information to make it more intelligible.
- 6. What can data visualisation do?
- 7. What can data visualisation do? Find stories in data that aren‟t possible to see from looking at a spreadsheet.
- 8. What can we visualise? Relationships
- 9. What can we visualise? Trends
- 10. What can we visualise? Change
- 11. What can we visualise? Change
- 12. What can we visualise? Geospatial patterns Source: Where America Lives, Time
- 13. What data do we use? http://moebio.com/newk/twitter/ “Big data”
- 14. What data do we use? Government Universities CorporationsInternational Organisations Unlock existing data sets
- 15. Why is this useful for people who want to create social change?
- 16. To uncover social problems and substantiate claims. Why is this useful for people who want to create social change?
- 17. Example: “Gentrification in Berlin is causing long- term inner city residents to be displaced to outer districts with more affordable rent prices.“ Is this true? Why is this useful for people who want to create social change?
- 18. Raw Data
- 21. Research solutions. Why is this useful for people who want to create social change?
- 22. Example: “How do we tackle the problem of rising global population?” Why is this useful for people who want to create social change?
- 23. Fertility vs life expectancy http://www.gapminder.org/
- 24. Fertility vs life expectancy http://www.gapminder.org/
- 25. Communicate Ideas. Why is this useful for people who want to create social change?
- 26. Example: “We already have the renewable energy technology we need to power the world sustainably.” Why is this useful for people who want to create social change?
- 27. Two Energy Futures 2035 energy mix International Energy Agency’s most likely scenario http://www.twoenergyfutures.org/
- 28. Two Energy Futures 2035 energy mix powered by existing renewable technologies http://www.twoenergyfutures.org/
- 29. Mythbusting Why is this useful for people who want to create social change?
- 30. Example: “Solar energy is too expensive.” Why is this useful for people who want to create social change?
- 32. Hold government and corporations to account. Why is this useful for people who want to create social change?
- 33. Example: “Which government departments answer the most FOI requests?” Why is this useful for people who want to create social change?
- 35. Where can we use data visualisation? • Internal decision making and campaign strategy decisions • Public awareness campaigns • Lobbying, whitepapers and research documents
- 36. Let‟s get started! says Simon Rogers, Data editor at Twitter, creator of the Guardian Datablog. http://simonrogers.net/2013/01/24/anyone-can- do-it-data-journalism-is-the-new-punk/ “Data Viz is the new Punk” “Anyone can do it”
- 37. So, we need an infographic... http://www.thinkbrilliant.com/infographic/
- 38. So, we need an infographic... http://www.thinkbrilliant.com/infographic/
- 39. Analysis of 30 most popular infographics on Visual.ly • Keep it simple: one main idea or message • Get your facts right • Shares from power users more important than design • http://blog.visual.ly/top-30-viral- infographics/
- 40. Analysis of 30 most popular infographics on Visual.ly • Timely or news related content • Observational, everyday life humour • Instructional or how to content Popular content types
- 41. Analysis of 30 most popular infographics on Visual.ly • Process chart • List Text • Single chart • Timeline • Repeated charts • Mixed charts Types of charts
- 42. Purpose • Be clear about your purpose before you begin. • It‟s like writing a thesis – you should be able to write your main idea or question on the back of an envelope. • Think about what questions you want to ask the data.
- 43. Purpose • Investigating and verifying claims • Mythbusting • Holding government or corporations to account • Showing the scale/extent/nature of a problem • Conveying solutions to a problem
- 44. Brainstorming • What fact shocked you when you first heard about it? • What have you always wanted to understand better? • What‟s a common misconception or myth you encounter? • What can we compare across time or across geography (countries, states)? • What facts do we need to hold governments and corporations to account?
- 45. Here‟s something we prepared earlier… • Social Media Week is trying to get 50-50 male-female participation. • We know that women are underrepresented in STEM. • Which countries have the highest and lowest proportion of female participation in STEM?
- 46. Here‟s something we prepared earlier… Find the data set After a bit of Googling... …we found a reference to a UNESCO report “A Global Perspective on Research and Development”.
- 47. Here‟s something we prepared earlier… Find the data set Their charts leave something to be desired.
- 48. Here‟s something we prepared earlier… Find the data set Can we find the original data? Yes! Go to: http://stats.uis.unesco.org/unesco/tableview er/document.aspx?ReportId=143 and select the “beta” data explorer.
- 49. Here‟s something we prepared earlier… Filter the data Filter the data set to only show us the most recent year. Download.
- 50. Where to find data • Government statistics • UN and other international organisations • NGOs • Corporations – may be limited in how you can use it • http://datamarket.com/ • https://code.google.com/p/google-refine/ • https://offenedaten.de/ • Guardian data blog
- 51. Cleaning the data • Work in Excel or free/open spreadsheet program • Most data will need to be cleaned up and simplified • Remove extra columns and rows, formatting • Possibly remove outliers or suspect data • Combine multiple data sets
- 52. Preliminary Analysis • Use the chart tools in Excel to quickly spot interesting trends • Pursue these in more sophisticated tools
- 53. Honesty With great power comes great responsibility! Data visualisation is a powerful tool –don„t use it to unintentionally or deliberately mislead.
- 54. Honesty • 3D tilted pie chart distorts the information. • Apple„s share of the market appears larger than it really is. http://www.theguardian.com/technology/blog/2008/jan/21/liesdamnliesandstevejobs
- 55. Honesty • Too many colours and poor layout makes the system appear overly complex http://blog.garrytan.com/epic-win-infographics-expose-republican-chart
- 56. Honesty • Anyone can do it, but it„s not always easy to do it right. • Take the time to learn basic conventions. • Be open about your methodology and data sources.
- 57. What chart for what data? Changes over time (trends) Line Graph or Timeline
- 58. What chart for what data? Relationship between two variables Scatter Plot
- 59. What chart for what data? Discrete quantities Bar Chart
- 60. What chart for what data? Categories and subcategories Stacked Bar Chart
- 61. What chart for what data? Relationship of part to whole Pie Chart
- 62. What chart for what data? 3 related variables Bubble Chart
- 63. What chart for what data? Processes Flow chart
- 64. Some things to be careful with... Circles Variables should determine area, not radius http://de.slideshare.net/vis4/making-data-visualizations-a-survival-guide
- 65. Some things to be careful with... Pie charts It„s hard to assess the relative size of areas
- 66. Some things to be careful with... 3D We have enough trouble understanding 2D
- 67. Some things to be careful with... Stacked area graph Use a stacked bar or line graph instead http://www.leancrew.com/all-this/2011/11/i-hate-stacked-area-charts/
- 68. Some things to be careful with... Heat maps Don„t just make a population map. http://www.thinkbrilliant.com/infographic/ Show densities and percentages, not absolute values.
- 69. Some things to be careful with... Heat maps Geographical space doesn„t equal population http://aidontheedge.info/2012/11/07/mapping-politics-and-the-politics-of-maps/
- 70. Some things to be careful with... Colour Breaks How you categorise data changes the story http://www.directionsmag.com/articles/choropleth-mapping-with-exploratory-data-analysis/123579
- 71. Some things to be careful with... Colour Breaks • Experiment at histagram.me • Upload your data to Google Spreadsheets then try using different break patterns
- 72. Some things to be careful with... Colour Breaks Jenks Natural Breaks http://histagram.me
- 73. Some things to be careful with... Colour Breaks Evenly spaced bins http://histagram.me
- 74. Tools • Tableau • Fusion tables • Datawrapper • Open Office • Data Explorer (Open Knowledge Foundation Labs) • Histagram.me • Javascript
- 75. Here‟s something we prepared earlier… Explore the data Upload to Google Spreadsheets. Tidy up blank rows etc. File>Publish to Web.
- 76. Here‟s something we prepared earlier… Explore the data Grab the spreadsheet key out of the URL. ?key=0AtPP45x7g3J6dEFmYjFkS1pqTEdp cFJQWnBKOHFOVVE
- 77. Here‟s something we prepared earlier… Explore the data Paste key into http://histagram.me. Explore different bin options (colour breaks).
- 78. Here‟s something we prepared earlier… Let‟s visualise! Download http://www.tableausoftware.com/.
- 79. Here‟s something we prepared earlier… Let‟s visualise! Connect your data file and drag and drop fields.
- 80. Here‟s something we prepared earlier… Let‟s visualise!
- 81. Here‟s something we prepared earlier… Let‟s visualise! Select your chart type.
- 82. Here‟s something we prepared earlier… Let‟s visualise! Display your data using custom bins.
- 83. Here‟s something we prepared earlier… Let‟s visualise!
- 84. Here‟s something we prepared earlier… Let‟s visualise! Edit colours and tooltips, and publish to the web.
- 85. Tone • Things that are shareable need to have more than a “wow – cool” attraction or they won‟t attract the attention of anyone except data nerds. • There must be a clearly articulated human story with an emotional tone. • Emotions = shares.
- 86. Tone Humour
- 91. Tone Make Big Stories Personal http://slaveryfootprint.org
- 94. Accessibility You can‟t completely replace a data visualisation for the vision impaired, but you should convey the key information in another way.
- 95. Accessibility - Colour Colour blindness affects 5% or more of the population. Don„t use a red-green colour scheme: http://colororacle.org/resources/2007_JennyKelso_DesigningMapsForTheColourVisionImpaired.pdf
- 96. Accessibility - Colour Create colour blind safe colour schemes using http://colorbrewer2.org/.
- 97. Accessibility - Colour http://colororacle.org allows you to add a “colour blind filter“ to artwork you are designing to check your work while in progress.
- 98. Accessibility Also think about: • People with cognitive disabilities (a simple text version) • People with poor internet connection or older computers (a no Javascript version) • Hearing disabilities if relevant
- 99. Here‟s something we prepared earlier… What‟s the story?
- 100. Here‟s something we prepared earlier… What‟s the story? What am I looking at? Why should I care?
- 101. Here‟s something we prepared earlier… What‟s the story? Germany lags behind in female participation in research.
- 102. The perfect data visualisation • Compelling title • Byline • Lead text that explains the story • Instructions for any interactivity • Where the numbers come from • Link to original source • Legends and labels as needed
- 104. Marketing campaign preparation Media pack Social media collateral Analytics Materials needed
- 105. Marketing campaign preparation Media pack
- 106. Marketing campaign preparation Media pack
- 107. Marketing campaign preparation Media pack Name of project URL (hyperlinked) One line summary Screenshot of data visualisation
- 108. Marketing campaign preparation Media pack Screenshot of data visualisation Something that conveys the essence of the images Detailed summary
- 109. Marketing campaign preparation Media pack Summary of key facts How does this interest your target market? Contact details (hyperlinked)
- 110. Marketing campaign preparation Media pack • Press release: 500 – 1,000 words • Images at various sizes
- 111. Marketing campaign preparation Social media collateral
- 112. Marketing campaign preparation Social media collateral Search Engine Optimisation (SEO)
- 113. Marketing campaign preparation Social media collateral Search Engine Optimisation (SEO) Title tag Meta description Keywords • clean energy • renewable energy • climate change • fossil fuels • unconventional oil • fracking • tar sands • shale oil • deep sea drilling • environment • nuclear power • biofuels
- 114. Maximum 70 characters Maximum 160 characters (155 to be safe) Pick keywords that are relevant to your campaign Marketing campaign preparation Social media collateral Search Engine Optimisation (SEO) Title tag Meta description Keywords
- 115. Marketing campaign preparation Social media collateral Twitter cards What is interesting? Why should I care?
- 116. Marketing campaign preparation Social media collateral Twitter cards Great! I love Whitney Houston! * Click *
- 117. Marketing campaign preparation Social media collateral Twitter cards More info: https://dev.twitter.com/docs/cards
- 118. Marketing campaign preparation Social media collateral Facebook Open Graph meta tags No Open Graph tags : No control over how content looks when shared.
- 119. Marketing campaign preparation Social media collateral Facebook Open Graph meta tags Open Graph tags : Control over how content looks when shared.
- 120. Marketing campaign preparation Social media collateral Facebook Open Graph meta tags More info: https://developers.facebook.com/docs/opengraph/
- 122. Marketing campaign preparation Analytics Google Analytics (visits)
- 123. Marketing campaign preparation Analytics AddThis Analytics (shares)
- 124. “Just one more thing…”
- 125. “Just one more thing…” What action are you asking people to take? Share
- 126. Marketing campaign What to include in your emails • A link to the data visualisation • A link to the image on Facebook (shared from your page so you also get likes)
- 127. Marketing campaign Who to contact • Friends and colleagues • Organisations who it would interest • Businesses who profit from your message • Articles/blogs focused on your area • Mainstream news sites • Facebook groups
- 128. Post campaign What to measure and report • Visits • Shares • Mentions in prominent media • Mentions in prominent blogs • Any other actions taken. For example, “target product stopped using palm oil.“
- 129. Resources • Guardian • New York Times • Boston Globe • Propublica • Flowing Data • Moebio • Tactical Tech • Open Data City • Mapbox • Open Knowledge Foundation Deutschland • Visual.ly • the functional art • Facts are Sacred • Accurat • OpenVis Conf • Google!
- 130. Thanks for listening! Presented by for littlewebgiants.com enquiries@littlewebgiants.com Now go and visualise some data...