Originally developed for big data and medium data contexts in the digital humanities, this method is currently also being used by tech startups, and in visualization of broader impacts by research groups in the humanities, sciences, and social sciences.
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What is your motivation to visualize?
Assemble a team
Who will help you meet that goal?
Ethically visualizing data is a team effort, requiring multiple roles that have traditionally been associated with vastly different disciplinary traditions and siloes of knowledge. Four recommended roles outlined below. Some of these skill areas may be found in more than one person. One or more people may fill each role. The more recipients are involved in the process, the better.
What data have you got?
Investigate through analysis
What can you find in the data using reason-led investigation?
Explore through play
What can you find in the data using intuition-led exploration?
Who needs it and how badly?
What is at stake in this visualization effort?
What is your motivation for sharing what you discovered in this data?
Identify intended and unintended audiences
Who do you want your visualization to reach the most?
Determine impact type
Which impact type will be most effective for your audiences?
What story makes it relevant to them?
Empathize with audiences
What are your audiences’ greatest needs?
What is the audience-oriented goal for the visualization?
What kind of story best achieves this goal?
Review narrative/framing literature
What does the literature say about this story?
How will you process and contextualize the data to tell that story?
What sources will you draw from?
Will the data hold up under scrutiny?
Is the dataset intelligible and navigable?
How does the frame need to be adjusted?
What visual data curation best conveys your story?
What platform, chart type(s) and data will visualize your story?
Determine media context
What is the most appropriate media context for your story to reach your audience?
Chooose chart type(s)
Which chart types tell your story effectively?
How can you arrange all elements so they can understand the story?
What design decisions will visualize the story effectively?
Adhere to design principles
Enforce visual consistency
How can you use titles, labels, and captions to reinforce the story?
Does your visualization communicate the story to your audience?
How can you guide them through the story with annotations, nudges, and animations.
Review visualization ethics literature
What are the latest ethical recommendations?
Does your visualization communicate the story to your audience better?
Why should they trust you?
Will publishing base data do harm to any intended or unintended audience?
Show process & affiliations
How can your ethical process be best demonstrated?
What is the felt impact of your published visualization?
How do the visualization’s intended impact and felt impact compare?
You can follow development of this work by subscribing to Dr Katherine Hepworth’s newsletter at https://broaderimpacts.substack.com.
If you’d like to contribute to the development of this work, please reach out at khepworth at unr dot edu. Referrals to other projects, literature, and methods that may be relevant are welcome, as well as suggestions for improvement or other modes of implmentation.
Have a high-stakes visualization you need to make an impact? There are a limited number of spots available for client work under the auspices of the Mick Hitchcock Ph.D. Project for Visualizing Science. To express your interest, reach out at khepworth at unr dot edu.
Hepworth, K. (2020). Ethical & Effective Visualization. https://zenodo.org/badge/latestdoi/232150677
From Hepworth, K. 2020. (forthcoming) “Make Me Care: Ethical Visualization for Impact in the Sciences and Data Sciences”, HCII Conference 2020 Proceedings.
The following institutions have supported development of this method.
I am grateful for discussions with and/or feedback from the following people. Their perspectives have led to the improvements outlined in the current version.
For more details of how each person contributed and contributions to previous versions can be found in the the full documentation list [here]acknowledgements.md.
This method is regularly updated. It is a key activity of Katherine Hepworth’s interdisciplinary research.
|Version 3.3||July 2020||Harm Reducing Visualization|
|Version 3.2||May 2020||Ethical & Effective Visualization|
|Version 3.15||May 2020||Ethics Checklist for COVID-19 Visualizations|
|Version 3.1||April 2020||Ethical Visualization for Impact|
|Version 3.0||March 2020||Ethical Visualization for Impact|
|Version 2.1||October 2019||Ethical Visualization|
|Version 2.0||October 2019||Ethical Visualization|
|Version 1.1||May 2019||Ethical Visualization|
|Version 1.0||December 2018||Ethical Visualization Workflow|