Data Visualization

Ethical Considerations for Analyzing and Visualizing Data:

Principles for a Questioning Lens, Venn Diagram. This graphic was created by the Visual Literacy and Resources Librarian at IU Libraries. Its content was inspired by the article, "Critical InfoVis: Exploring the Politics of Visualizations". Please see the full citation for the article at the bottom of this box.

Principles for a Questioning Lens:

In the article, "Critical InfoVis: Exploring the Politics of Visualization," Marian Dörk and co-authors propose a set of guidelines for creating and reviewing visualizations ethically. These guidelines are called, Principles for a Questioning Lens.

Disclosure: 

It is very important for those working in data science to establish trust with their viewer. Specifically, this refers to the visualization creator being explicit as to what content and design choices they made and why they made them. 

Plurality:

It is impossible for one visualization to record all perspectives on a topic. But, it is helpful for a visualization creator to include as many perspectives on a topic as possible in the design process. This allows for multiple interpretations of the visualization and engagement with the viewer.

Contingency:

It is important that visualization creators don't design with a pre-determined conclusion in mind. Visualization creators can avoid this by acknowledging the positionality of the viewer in relation to the topic of the visualization.

Empowerment:

Visualization creators should encourage their viewers to think critically about the visualizations they create. Viewers should be able to question the choices of the creator, think critically about the information shared, and relate to the topics discussed.

Questions to Consider:

• What are the credentials of the visualization creator? Do they have the experiences and knowledge necessary to create a visualization ethically?
• Is the creator taking into account the perspectives and experiences of those personally connected to this data?
• Is the visualization appropriate for the audience? Does it seem like the visualization creator took the information needs and experiences of their viewers into account when designing?
• Whose goals and interests are prioritized in the visualization? Is there anyone missing?

Resources:

Correll, Michael. "Ethical Dimensions of Visualization Research". Paper at CHI Conference, 2019.

D'ignazio, Catherine, and Lauren F. Klein. Data Feminism. Cambridge, MA: The MIT Press, 2020.

Dörk, Marian, et al. "Critical InfoVis: Exploring the Politics of Visualization." Paper at CHI: Changing Perspectives, Paris, France, 2013.