In art and literature, "criticism" doesn't mean "pointing out flaws." It's something bigger and more interesting than a referee calling fouls. I think we should have the same ambitions for data visualization criticism!
Comments
Log in with your Bluesky account to leave a comment
Exactly—criticism should be an act of exploration, not condemnation. In data viz, it’s about uncovering hidden stories, challenging assumptions, and sparking better design. Less like a referee, more like a co-creator.
In cartography, critique is critical but often mistaken as criticism which can be problematic. Effective critique points to ways work might be improved. It relies on discussion, understanding, and justification. Crucially it needs all involved, with knowledge of what critique is, and what it isn't.
A classic example of what I think is great criticism: Tufte's discussion of "small multiples." He spotted and named a powerful existing pattern, and connected it to big themes, like the importance of comparison. This kind of criticism helps us understand, build, and talk about visualizations.
It's unclear to me how this constitutes criticism? It seems like this is a different form of engagement and meaning-making that is of course extremely valuable but not what would traditionally fit the definition of criticism. Or maybe I don't know the backstory well enough to see the connection.
Here's an analogy: when I first heard the term "unreliable narrator," a certain aspect of fiction just snapped into focus for me. It changed the way I read and think about stories. That term was introduced in a famous book of literary criticism! "Small multiples" had a similar effect on me.
I understand you clearly now. The entire work is "criticism" and within criticism are structures and claims made by the critic that are not maybe critique in the vernacular sense but actually creative in a dialectical sense. That's a very high bar though what if I only have time to point out flaws?
I think it goes beyond descriptive and actually is actively creative but I like this spectrum (that I probably should have intuited already and feel a little silly for missing):
A contemporary example is from @kanarinka.bsky.social and @laurenfklein.bsky.social in Data Feminism, in their analysis of visualizations that "elevate emotion." I regularly assign this work because it visibly expands the way students think about visualization.
Data Feminism and Envisioning Information certainly do point to flaws in other work (in the case of Data Feminism, this includes Tufte's books, perhaps making it an example of "criticism criticism"!) But that's just a means to more important ends.
Yes! Though I think redesign is one excellent tactic, it's not the only one. That said, there's nothing like attempting a redesign to give you sympathy for the original creator.
Amazing point. Many people think criticism means “I hate your music” when it’s meant to be constructive. It’s really rough this day and age with short form content because true criticism needs true understanding and that’s not possible to express to people who have a 1 minute attention span
The 2nd is actually directed at the maker, and in a way, does "point out" what could be strengthened/isn't working in the work. (Art school critique from studio critic)
I think viz can benefit from both but conflating the two — a picking apart outside of a mentoring relationship ostensibly as an object lesson for the public in short form social media....personally I'm extremely dubious about the efficacy of that moving any kind of needle anywhere.
Comments
#DataViz
#CriticismAsArt
#DesignThinking
https://bsky.app/profile/sonjakuijpers.bsky.social/post/3ler3vbajkc2s
prescriptive <-> descriptive <-> creative (dialectical)
We might need to start using the difference between criticism (pointing flaws) and critique (analysis).
One whose intended audience is the public, usually in the form of long-form writing that seeks to interpret art for the public. (E.g. Art Forum)
We learn through the act of synthesis and participating in discourse, not through classification into 'good' and 'bad'.