The three readings for this week all come more or less under the rubric of "best practice". While it could be said that all three share common themes, the two shorter posts from "Visualization" both read as more functional and utilitarian which would make sense given their demographic. The last from "Data Visualization for Social Science" is certainly a more nuanced approach and incorporates into its argument matters of historical record, physicality and psychology.
The first from Visualization: "Misleading axes on graphs", encourages readers, similar to Drucker, to regard the act of codifying data visually as a conscious process of telling a story. The choices we have for example, including (or not) a zero point in a bar or line chart, determine what story we are telling and how we have chosen to tell it. While in some cases there may be good reasons for deviating from the norm, in the vast majority of cases assayed here, the root cause is most likely disingenuousness or in the best case, incompetence. The takeaway is ultimately the line graph is a visual tool used to show deltas in variables while bar graphs are better for asserting magnitudes.
The second of the two, while equally informative, was perhaps the most entertaining highlighting a parade of bad faith or simply awful counter-examples to the principle of "proportional ink". The main focus of this piece is that the amount of ink used represent a data point should conform to a direct proportion of its value. Attempts to fulfill secondary objectives (Ex: making the visualization more interesting by the use of 3D bar charts, donut charts, etc.) should be avoided if (as they often do) they tend to obscure the viewer's perception of relative or absolute values in favor of visual spice.
The last article, and my favorite, considers what limitations we as consumers of visualizations have and what of these points should be incorporated into any ethical/functional considerations. Additionally as producers of such stories, what ethical choices we face when we omit data or use the wrong tools/bad data to support a story we would like to tell.
Again the theme of prioritizing aesthetics vs clarity is revisited. That said, of most interest to me were the sections dealing with geometric and physical limitations of perception (I'm currently reading "Thinking Fast and Slow" by Daniel Kahneman with several thematically similar chapters). Taken as a whole, these are issues that defy any sort of remediation. The fix in almost all cases is simply "don't do that" since the problem is one of how humans are physically instantiated and not one of policy or ethics. We are simply wired to respond more or less positively to various rhetorical assertions based on how they are encoded.
In contrast to their original assertion that a "boiled down" list of principles it's difficult to enumerate, I was grateful for the section on the Cleveland and McGill study. While I understand the concern, being provided a model framework is useful until I can internalize it well enough to understand when exceptions are reasonable. To this end (and in response to these blogs) I have already considered several times how I might remake our first two assignments in light of these guidelines and how my usage either supported or violated best practice.
Honestly, as subjects for response papers, there wasn't much here to debate. Every point is well-taken and I appreciate the skill required to bring this in an understandable fashion to non-experts. I look forward to being able to use these pointers in future class projects.