Tasting data

Tasting data! Crazy idea? I thought so too, until I attended the inspiring talk by Benjamin Wiederkehr about “The shape of data” at the Interaction 2023 Conference last week.

Benjamin shared that we can and should design for all the human senses to make data interactions more inclusive, enable a wider audience to communicate and perceive data, and to create a long lasting impact beyond the data artefact.

These are my takeaways from the talk.

We need to create inclusive interactions with data, because data…

• Is essential in raising questions and solving problems.
• Is used to change how we practice science, generate economic value, define policy or conduct societal discourse.
• Is used in opinion shaping, decision making, and knowledge building

Sobering reality

• There is an issue of exclusion in today’s data culture. Because: Only certain groups of people speak data, but the vast majority don’t speak data. Anyone who doesn’t speak data is left out of certain kinds of processes and conversations.
• We put the burden of overcoming the exclusionary nature of today’s data culture onto the receiver: improving their skills, their attitudes, their knowledge.
• We rarely consider changing the channel to better fit the essential features of the sender and the receiver.

Root cause

Many of today’s design solutions are limited to dominant and technocratic tools and techniques: tables, charts, reports, dashboards. They accurately translate the statistical facts, but fail to connect with the audience on a deeper, more human level.

How can we make data interactions more inclusive?

Design different approaches to engaging and interacting with data that use all our human senses.

Sight: Visualization. Making data visible.

Data visualization is not a new practice. Examples from the 18th to 20th century look similar to the ones today. But data is being used in new contexts beyond the report and the dashboard. Example: Isokinetic exercise routine: visualization show athlete’s performance and act as a visual stimuli to push the athlete’s progress.

Hearing: Sonification. Making data audible.

This uses simple signals, melodies, and complex soundscapes.

Examples:
- Geiger counter: electrical instrument to detect and measure radiation.
- Sonar: technique to determine the distance, angle, and velocity of objects
- ECG: recording the heart’s electrical activity through cardiac cycles.
- A complex soundscape that communicates the concentration of carbon dioxide in the atmosphere as a humming sound, and average global temperature as a ping pong sound on top. (Created Chris chafe at the Stanford Center for Music and Arcustics.)

More examples can be found in the Data Sonification Archive at the Centre for Design at Northeastern University, and from TU Delft at sonification.design.

Taste: Tastification. Making data smellable.

Uses the inherent forms of food: color, form, texture, smell, taste, nutrition, origin, etc. as a communication tool.

Example: 1–2 day Data Cuisine Workshop. Participants explore local open data in local food. Data experts had worked with a local chef turning data into dishes. Example dishes: Slices of pizza visualizing the energy mix used in creation of an object. Dessert with melting ice caps.

Smell: Smellification. Making data smellable.

Example: The The smell of data project. Using scent to alert users to data leaks on personal devices.

Touch: Physicalization. Making data tangible.

Example: A physical map composed of 3400 handwritten tote tags that represent migrants who have died while crossing the desert. (Created by Participatory art project “Hostile terrain 1994” by the undocumented migration project.

More data physicalization examples can be found on the data physicalization wiki dataphis.org.

Proprioception: Spacialization. Making data a bodily experience.

It is a bodily experience, because there is no artifact here to see or touch. The data is perceived in how we relate to others in the space around us.

Example: Participatory theater play where people are an individual data point who get ordered/categorized based on certain attributes: age, gender, political leanings, etc

Conclusion

Data interaction is less about the artifact, and more about creating and sharing the data artifact together. The artifact is short-lived, but the experience and memory from co-creation of the artifact has long lasting outcomes.

Call to action

1. Design for all senses and abilities to enable accessible, inclusive, and intuitive interactions with data.
2. Use more diverse formats beyond the prevalent and dominant ones.
3. Get people of all backgrounds to participate in the creation of data interactions.

Photo by Patrick Fore on Unsplash