Rdviz-culture

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)

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

Personas, use cases, context

Catherine Dignazio catherine_dignazio@emerson.edu @kanarinka

Kate Hotler @KateLovesUX

Andrew McWilliams @jahyadotnet

Jon Schwabish @jschwabish

Gabi Sobliye @seeingsideways