Difference between revisions of "Rdviz-culture"

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** Problem: Data visualization can exclude by taking and not giving back
 
** Problem: Data visualization can exclude by taking and not giving back
 
*** form is not legible to the community
 
*** form is not legible to the community
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*** dataviz is not shared at all
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*** doesn't engage the community (about, but not for or by)
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== Contributors ==
 
== Contributors ==
 +
 +
Catherine Dignazio
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catherine_dignazio@emerson.edu
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@kanarinka
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Kate Hotler
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@KateLovesUX
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 +
Andrew McWilliams
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@jahyadotnet
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Jon Schwabish
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@jschwabish
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Gabi Sobliye
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@seeingsideways
  
 
== Resources (we <3 links!) ==
 
== Resources (we <3 links!) ==
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* http://civicmediaproject.org/works/civic-media-project/index
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* http://helpmeviz.com/
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* http://www.amazon.com/Whistling-Vivaldi-Stereotypes-Affect-Issues/dp/0393339726
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* https://civic.mit.edu/feminist-data-visualization

Latest revision as of 01:37, 16 January 2016

Outputs

Description of a minimum viable product, aspirational output, stretch goals, etc. Collaborative website: The Inclusive Data Visualization Project

Tabs

  • What is inclusive data visualization?
    • Here we ask visitors to submit their comments about what they think of when it comes to having an inclusive data visualization field
  • Exclusion by Access
    • Problem: Data visualization can exclude due to issues of access, including
      • bandwidth and connectivity
      • language/layout of tools and resources
      • discriminatory hiring practices
  • Exclusion by Misrepresentation
    • Problem: Data visualization can exclude by misrepresenting people, along the dimensions of
      • gender
      • ethnicity
      • location
  • Exclusions by Extraction
    • Problem: Data visualization can exclude by taking and not giving back
      • form is not legible to the community
      • dataviz is not shared at all
      • doesn't engage the community (about, but not for or by)


  • Each page has space for case studies, tools, resources, and other links

Notes

Culture (producers and consumers)

Possible Outputs

  • Cultural checklist or guide
  • Mentorship program (physical/virtual meetup space)
  • Human-centered design for dataviz
  • Manifesto
    • Active discussion tool/platform (wiki?)
    • Open source tools
    • “The Manifesto of the Missing People”
  • kids, African, Asian, etc.
  • here is the list of people who are not here
  • how do we start to include them?
  • Resources of/for people who have agreed to abide by it
  • “I’ve agreed to commit to this as part of my practice”
  • Tap into featured people who are already in the conversation
    • The Inclusive Data Visualization Project
  • Tell by showing—case studies; blog posts
  • Tools
  • Link dump/Resource page
  • Checklist
  • Access—low bandwidth, no English
  • Not seeing themselves in the data—gender, race
  • Seeing themselves in the eyes of others
  • “a sketchpad for people to say, ‘this is what I think inclusive data visualization looks like.’” ← as a sheet on the science project
  • Who is this for?
  • Practitioners
  • What do we want them to do?
  • This is what we know; what do you know?
  • Mission statement
  • Series of blog posts
  • Research agenda (wiki?)
  • Early ed. Curriculum
    • Baseline data/graph literacy
    • Exercises targeted to different cultures
    • Treat data visualization as a core standard
  • Post-secondary education
    • Interdisciplinary?
  • Different dataviz mediums and how they are used and understood by different groups
    • most efficient engagement tools for different groups

Audience

Personas, use cases, context

Next steps

Contributors

Catherine Dignazio catherine_dignazio@emerson.edu @kanarinka

Kate Hotler @KateLovesUX

Andrew McWilliams @jahyadotnet

Jon Schwabish @jschwabish

Gabi Sobliye @seeingsideways

Resources (we <3 links!)