Data visualization: can art historians use Excel?

This week has been all about data visualization and its ability to clarify abstract data and aid in our ability to read and absorb large amount of it. I’ll admit I was skeptical when we began our workshop in this section of the course with Excel, but I am now convinced that these tools do actually have something to offer art history. It’s important to note that although I associate Excel with middle school science projects and finance spreadsheets, both the information (the data) that art historians are displaying and generally the types of charts or visuals we are creating are quite different.

When I think about data visualization in the context of art, I think immediately of Guerrilla Girls. I wasn’t going to focus on this connection since I have tended to focus on artists using digital tools rather than art historians in my blog posts (see my last post here), but Taylor’s comment on my last post made me realize that this is actually important as artists’ use of these tools will serve as an important impetus for art historians to get on board the digital history train. Anyways, back to the Guerrilla Girls’ use of infographics and data visualization. Take for example their “Bus Companies Are More Enlightened Than NYC Art Galleries” graphic that shows the percentage of women in various jobs. The percentages themselves are easy to understand, but I think it is an instance where a graph may help to really show the discrepancies. Many of their charts and “report cards” have the potential to be visualized in this way as well. For now, I’ve taken the liberty of making a very rudimentary graph for this one graphic.

I’m definitely not providing new information or really asking any new questions with the graph of the “data” from the image, but I think it is perhaps easier to read. Having both images is redundant, but perhaps incorporating data visualizations into their infographics would be a good strategy for the Guerrilla Girls.

Let’s take a (small) step back into some theory

I think the question of “am I asking or answering any new questions” is important. In my Guerrilla Girl example, I was not, and honestly I’m struggling to think of a way that a lot of these data visualizations would ask new research questions in and of themselves. A good way to think about this conundrum would be the questions posed by Shazna Nessa in “Visual Literacy in an Age of Data,”  :

• Who am I creating this for?
• What journalistic impact should the visualization have?
• If I opt for novel graphical/interaction styles, what guidance will I provide the audience?
• Should I blend exploratory aspects with explanatory aspects?
• How will I expose the story?
• Can I add a narrative, causation information, or a news peg?
• Although I’ve edited the data already, is there superfluous data that I can still edit out?

Although these questions aren’t necessarily specific to art history, I think they are interesting and vital to interrogating the role of visualizations in the field. I’d propose the addition of a few other questions: Is this visualization asking a new research question or answering an established one in a new way? Is the information that it is sharing already explained clearly enough in my writing and therefore is it redundant? There are so many visualization tools — charts, word maps, image charts, the list goes on– that it is tempting to include at least one in your project. You can easily make one of the visualization types work for your project, but should you? I’m not convinced that just because these tools can work for our discipline that they belong there. They seem to live squarely in the history side of the field rather than the art. To me, if we are to include graphics in our research, it seems best to include images of the objects we are exploring rather than graphics that visualize what we are saying about them.

So I tried to make a few visualizations…

And honestly, they didn’t turn out too well. In class we played around with the Tate’s data on the artists and artworks in their collection. This is a lot of data to handle, so usually we tended to break up the data into more manageable groupings. For example, I tended to not only to just focus on the “A’s” (meaning artists whose last name started with A), but even just a small set of those artists. First I poked around with Excel and couldn’t really make any visual aids that I thought were useful enough to include here. We did make a pie chart of male vs. female artists, which could be helpful. However, we had to switch the data input to be able to chart this. We had to switch the word “male” or “female” in the column to a numerical datapoint that the computer could add up, which was hard necessarily, but definitely took up time. Next we worked with Tableau. In some ways, I found Tableau to be a bit more intuitive, but I still struggled with this assignment. A lot of these struggles may be because I didn’t really have control over the data collection and data set. It may have been easier had I gotten my own data and chosen the fields more carefully to be able to structure my visualizations around a certain argument. In the end I only made a few visual aids that I thought could be useful. I managed to make the following graph that looked at how many pieces in a certain media various artists had in the Tate collection. Including ALL the artists in the data set was unwieldy, as was even just focusing on the A’s, so here is an instance that I included only 30-something of the artists whose last name started with A.

My main issue with the graph is aesthetic. The way the artists’ names appear on the top is unclear and hard to read. I could have used fewer artists to alleviate this, but then I don’t get to compare as many artists which limits the scope of my research. It is interesting to see the distribution of media in the collection, and this graph definitely does show that pretty clearly in the length of the bars, but I’m not sure it was worth the data manipulation. A simple chart or a paragraph of text could probably achieve the same result.

I want to return back to those questions posed by Nessa to evaluate my graphic. Who am I creating this for? I could be creating this graphic for an acquisition committee. It could be useful for the board to see what holes there are in the collection and to determine if another oil painting or print by a certain artist is really a necessary purchase. This visualization may be useful in that boardroom setting when making decisions if the members don’t have a firm grasp of all the items in the collection (which is nearly impossible with a collection the size of the Tate’s). What journalistic impact should the visualization have? Going forward with that acquisition committee example, this graphic should demonstrate the breadth of the collection and act as a simple representation of the distribution of media and artists’ works. If I opt for novel graphical/interaction styles, what guidance will I provide the audience? I think this is an important question for this particular graph. I would need to perhaps supplement with text outlining where the pieces came from (if groups of prints were bequeathed together for example) and when they were acquired by the museum. This historical acquisition data would be necessary to understand the graph. How will I expose the story? I would include that contextualization first and then turn to this graph to reiterate a point rather than begin with it. This would incorporate the narrative quality in another one of Nessa’s questions. Although I’ve edited the data already, is there superfluous data that I can still edit out? Here I think I’ve edited out the superfluous data. But even if I didn’t think I had, Tableau requires a certain number of fields to create certain graphic types, so I needed to include what I did.