Data, and stories on race and equity issues in the U.S. can reveal disparities and injustices while emphasizing the need for progress and change. To empower organizations and individuals from both the national and community level, we must increase their access to clean and usable data. This is the gap we hope to address through your contributions to the Tableau Racial Equity Data Hub.
Contributors to the Hub will build Tableau visualizations to illustrate racial disparities and opportunities for change in many forms across these issue areas:
All organizations and individuals involved must use data ethically. Lead with respect, keeping in mind that data represents real people—who can be helped or harmed as a result of how the data is used.
- Submit projects to email@example.com
- Confirmation email will be sent at time of submission.
- Submissions will be reviewed by our Advisory Board on a rolling basis.
- Selection will be based on the project’s potential to advance credible data stories about race in America, and support capacity-building for equity-focused organizations who use data in their campaigns.
- Contributors will be connected with equity and visualization experts, as appropriate, who will help refine visualizations that align with our core issue areas.
- Projects must be completed 1 month (unless negotiated otherwise) after you are connected with visualization experts by Tableau.
- Visualizations must be configured with a mobile-friendly interface to provide proper accessibility.
- Contributors must complete the content guidelines that describe all the data sources being used, the visualization details, and the story the organization/individual aims to tell.
- Projects must be submitted with both the Tableau Public link and the corresponding content guidelines.
- Submissions are evaluated by both the Racial Equity Data Hub team and the advisory board.
- Questions, concerns and recommended revisions will be provided to the contributor.
- After final approval, the Tableau Public link and the corresponding context language will be uploaded to the Racial Equity Data Hub.
- Please title your visualization.
- The data: Describe the datasource(s) you used, and why. Discuss any analysis or cleaning of the data you had to do to work with it.
- The visualization: Describe the visual choices you made to present the data. What did you want to highlight, and how did you use the viz to convey the information and insights from it?
- The historical context: Describe what history/policies are behind the data presented in the viz. This is critical for making the point that while the data visualized may reflect reality, that reality is the product of decisions and policies that produce inequities.
- The implications of the data: What is meaningful about this data in the present-day context? What does it show and why does it matter? How could an advocate use this viz and data?
- Takeaways: Provide two to three key insights from the viz that could form the kernel of a story.
Here is an example of a contextualized visualization:
Here is an example of the way your viz will be situated: