You can download the slides from Geoff McGhee’s presentation “Getting Started with Data Visualization” here.
Discuss the material for the chapter on Data Visualization below.
I was glad to note, in this week’s reading, that there’s a trend toward making the datasets underlying new visualizations available for download. This move toward transparency is laudable.
It does raise another question — are there mechanisms in development, yet, for peer review of this sort of interactive material? I suppose some curmudgeon could go around downloading data-sets and deconstructing published visualizations in his or her field systematically, but it seems like there’s very little incentive for anyone to do this. In fact, the interactive options to generate states make it even less likely for most comers to engage with the underlying data set, but rather invites them to dive in searching for evidence that supports a thesis without evaluating the underlying structure.
Assuming that some equivalent to peer review will happen after publication, as one can assume that readers will chime in to correct factual errors on a website like Wikipedia that deals with subjects of wider public interest and with a much larger reader base, seems problematic.
One area of data visualization that concerns me is the reception of an increasing use of these visualizations by the general public. While visualizations can play a tremendous role in making information much more accessible and understandable to the general public, it seems to me that the opportunity to mislead, whether purposefully or through poor choices in making a visualization, is also an issue. To the uncritical observer, visualizations have a certain infallibility about them. This is perhaps compounded by (in my view) the focus of our educational system on critical reading of text over critical analyzing of visuals. As technology gives us an increasing use of visualizations, it will be critical that we have an education system that responds by focusing more attention on understanding these visualizations. Only with a properly critical and educated public can these visualizations be most effectively, and honestly used to accurately inform.
I certainly agree with Michael’s observation that visualizations can be misused and deceiving to an audience. It seems issues surrounding data visualization are similar to those with PowerPoint where many critics claim the ornate graphs and charts confuse the issue rather than relying on straightforward tables. One study noted that when a football recruits statistics were presented through PowerPoint, analysts gave the potential recruit a higher rating than when the same data was presented in hardcopy. Is it possible academics will similarly rely on elaborate visualizations to lend undeserving credibility to their findings or inflate their certainty?
To perhaps sound an even more cynical strain on the note of the illusory “objectivity” of visualizations, shouldn’t academics and journalists producing these graphics be a bit wary of falling into the trap of assuming an immutability or an aura of power around visualizations of data themselves? After all, there are and have been clearly many institutional, material, and cultural obstacles even for those of us in the “e-generation” toward learning to use (without abusing!) rapidly proliferating technologies. Nile, your point about Powerpoint really strikes home with me–the problem of misusing that application, whether by simply reproducing one’s speech onscreen and reading it aloud or by obfuscating information with visual or aural pizazz, is widespread not only among the populations one might (fairly or not) expect–older users who grew up with longhand and typewriters–but also among current undergraduates. As the workshop has continued, I am increasingly struck by the urgency of addressing unequal access to and education in the use of digital tools for condensing, processing, and understanding information.
I totally agree with Yvon above re: the urgency of educating scholars in (even a basic) data visualization/presentation skill-set, and I’m glad Stanford has the resources to help teachers and would-be teachers acquire those skills—I know I now plan to take one of the courses offered for this very purpose. And I wonder if the urgency of this literacy—really, literacy in all aspects of digital humanities—won’t become even more urgent as the humanities are increasingly undervalued and effaced in the US. Taking Hans Rosling’s exhortation of “no more boring data” to heart should serve us well, regardless of the data’s content.
“shouldn’t academics and journalists producing these graphics be a bit wary of falling into the trap of assuming an immutability or an aura of power around visualizations of data themselves?” Yes, obviously. A reason to hope, I think, is the proliferation of hackers in the newsroom and, to some extent, a flow in the other direction, too. Columbia recently began offering a joint degree in journalism and computer science. The more that academic disciplines and professional fields can inform each other of their values, standards, precautions (e.g., opening source code or data for readers to inspect) and so on, the better off I think we are in figuring out, together, a way to put data to work in public discourse, for broad audiences. (One of my favorites: The Texas Tribune, where I interned last summer. See http://www.texastribune.org/library/data/)
I agree with Michael and Nile. Visualization is extremely powerful in demonstrating what can be too complicated to convey by words, but visualization can be distorting facts as well. Moreover, it can be extremely costly to do. What kind of information that is most suitable and necessary to be conveyed by digital visualization?
As I said in “spatial analysis” section, I am still concerned about the proportion between cost and reward in a visualizing project.Republic of letters is an amazing and exciting presentation,but I would like to know more about how many new arguments people are forming from it and how much these arguments are rectifying our stereotyped opinions gained from traditional scholarly approach. In other words, I do hope to see a perfect combination of visualizing project and a verbalized argument. The marriage of the two is not only a matter of inter-disciplinary collaboration between humanitarians and scientists, but also a matter of the genuine analytical power of the visual—if they are something more than an eye-catcher.
Touching on many people’s comments, while I agree that visualization is really interesting to look at, I do fear that it can have a negative impact on the data being presented. Information can be misconstrued. Or presented in a “biased” manner, and as that may be one’s only source of information, lead to misinformation. Details may be left out. Especially considering today’s emphasis on analysi, as seen in the Text Analysis workshop, I am scared that Data Visualization may be too much of an analysis that is not open to interpretation, unlike text analysis where each person can take their own view. I feel that doing so with visualization may be much harder.
On a more positive note, one of the uses for data visualization that hasn’t been talked about in the comments is as a part of the researcher’s own process. When working on humanities projects where I need to look at trends or data (even just within one book) I find it helpful to create basic charts or graphs, regardless of whether I use them in the final product. This type of digital visualization can help organize your observations and give you more concrete ways to talk about fuzzy or qualitative changes in text.
Also, my favorite link from the further reading/viewing section for this week was “Modern approaches to Data Visualization.” It’s a great overview of a bunch of different website and programs!
Hoping late is better than never . . .
I agree with what others have said. One need only watch Fox News to know how data may be manipulated, and although I found it mesmerizing to watch the various visual representations change on the PowerPoint screen during our last discussion, it made me wonder just how we are supposed to check ourselves. Hardly any of us have degrees in statistics (and some of us are downright mathphobic). I see the potential for it being extremely useful, but also for the abuses of it, as well.
I think the issue of peer review is going to get very sticky in the next ten years, not only in digital humanities, but in other areas as well, as we explore different ways of presenting research. It may very well be that there is a huge sea change in the works that none of us are even aware of yet.
I do agree with Helen He and her concerns about the proportion between cost and reward in a visualizing projects. In addition, I have to admit that in my field of study, or rather in my own research I rarely have the chance or the need to visualize my data. It was very interesting to be informed about the different possibilities and obviously data manipulation is an important issues. Nevertheless, I don’t think that these tools will be very important in my studies.