As art librarians and students, we are especially aware of how digital resources and the Internet have changed art scholarship. I find myself recommending academic streaming music databases to performing arts students who, ten years ago, would have had access only to CD recordings; For a close-up look at The Scream painted by Edvard Munch, I send students to Artstor before digging out a print catalog; When developing library instruction sessions, I nearly always use a digital presentation component like Google Slides or a video tutorial hosted by Vimeo or YouTube. But, one of the emerging digital trends in academia that I find most engrossing is data visualization or information visualization.
As Autumn Wetli discussed in her ArLiSNAP article The Practice and Problems of Digital Art History
, several digital programs exist that allow art historians to analyze research text, data, or image collections and then present visual representations of that information or findings therein (Wetli, 2017). This is data visualization. Elegantly explained by data visualization specialist Alberto Cairo, a visualization is “a graphical representation designed to enable exploration, analysis, and communication” (Cairo, 2017).
For art researchers, the application of data visualization in a digital environment offers infinite possibilities. Graphs, charts, data maps, and other visualizations, when incorporated into research, can make an article more appealing or make an argument more persuasive (Cairo, 2017). And, in the age of interactive and socially engaging digital media, scholars who study art are at a unique advantage to produce colorful, media-rich, graphically stunning visualizations. (Glassman & Dyki, 2017).
Apart from the potential of art scholars to integrate images of art into their visualizations, the changing nature of scholarly publishing in the fine arts signals an era of change for how data is represented in art scholarship and how art researchers can move forward in an informed way. In a 2017 article entitled “Beyond the monograph? Transformations in scholarly communication and their impact on art librarianship,” Patrick Tomlin details many of these changes. Digital models of publication present an advantage due to the potential for institutions to take greater control of internal publishing, the benefit of open access, the increasing cost of full-color print monographs, and the growing importance of search engine discovery (Tomlin, 2017). From the perspectives of emerging art librarians who will take an active role in research and instruction, having a basic understanding of data visualization and its increasing presence in the world of digital art history is crucial.
To facilitate a basic understanding of how one might introduce data visualization to new art scholars, I have compiled this guide. These ideas serve as an introduction to data visualization for both the librarian and the researcher, who together can learn to apply existing knowledge of art scholarship towards this goal.
First: It is advantageous for the instruction librarian to introduce (or re-introduce) students to the principles of visual literacy. To create one’s own visualizations, scholars should be well-versed in visual communication. Online tools like Image Atlas may serve to prepare students to understand bias and perspective in images (Bailey & Pregill, 2014, p. 183). I will link below to a 2012 article by Tammy Ravas and Megan Stark which provides an informative case study in teaching “the ethics of seeing” (Ravas & Stark, 2012, p. 41). Instructors may find that integrating visual literacy lessons into existing information literacy lesson plans bolsters students’ understanding of visual literacy when applied to the eventual creation of their own data visualizations (Ravas & Stark, 2012, p. 35).
Second: Just as digital art history scholars should be visually literate, they should also be data literate. In his 2017 lecture at the Cornell University Library, Alberto Cairo details a study from the Pew Research Center, which concludes that many people who read articles that contain data visualizations do not know how to correctly read scatter plots, bar graphs, and line charts (Cairo, 2017). Though this study focuses upon popular media, the importance of an understanding of the interpretation of data can not be understated for scholarly communities. In a 2012 article in Art Documentation, Victoria Szabo emphasizes the value of data literate art historians who know how to use and organize data. She states that “Faculty and staff technical advisors sometimes unfamiliar with the research domain, even if experienced in humanities collaborations more generally, may not realize the extent to which their biases and assumptions for how to clean and standardize data could compromise the intellectual integrity of a project. Variant spellings, for example, could be important in tracing the provenance of a particular art object” (Szabo, 2012, p. 171). Interdepartmental collaborations with information technology staff may allow librarians and art faculty to learn more about data management programs, software, methods, and training.
Third: Creating one’s own data visualizations does not mean learning how to program Java or code HTML. For art historians who are just learning how to create visualizations, there are a number of free programs which exist to assist them. It may be beneficial to design instructional lesson plans around visualization software with which students are already familiar. I would suggest choosing a sample research topic within a class curriculum to be plotted in Google Maps. Topics like “locations of art auction houses in Paris” or “art galleries in New York during the Harlem Renaissance” may serve to develop simple exercises that illicit broader understandings of in-class research. Paul Glassman and Judy Dyki’s Handbook of Art and Design Librarianship, 2nd edition, contains several resources on using map plotting in art history research.
Once students have outgrown this more familiar tool, they can move on to greater objectives, like creating visualizations using the immense capabilities of Google Charts. They can practice embedding these visualizations into Wikis, LibGuides, or social media. And, they can explore increasingly sophisticated tools like ImagePlot while developing their comfort level with visualization technology.
Data visualization may seem like a daunting undertaking for researchers who have been educated mostly in text-based scholarship. But, the implications of having an understanding of visualizations in digital art history are immense. For art librarians who are increasingly tasked with the education of scholars in a digital field, I hope that the tools and ideas I have outlined may provide a basis of knowledge for teaching this emerging technology. I truly believe that, if introduced to the field of data visualization within the parameters of their understanding of visual literacy, data, and art scholarship, researchers will learn to be excited about the potential of data visualization to enhance and embellish their research work.
Bailey, J., & Pregill, L. (2014). Speak to the Eyes: The History and Practice of Information Visualization. Art Documentation: Journal of the Art Libraries Society of North America, 33(2), 168-191. doi:10.1086/678525
Glassman, P., & Dyki, J. (Eds.). (2017). The Handbook of Art and Design Librarianship (2nd ed.). Chicago, IL: ALA Neal-Schuman.
Ravas, T., & Stark, M. (2012). Pulitzer Prize Winning Photographs and Visual Literacy at The University of Montana. Art Documentation: Journal of the Art Libraries Society of North America, 31(1), 34-44. doi:10.1086/665334
Szabo, V. (2012). Transforming Art History Research with Database Analytics: Visualizing Art Markets. Art Documentation: Journal of the Art Libraries Society of North America, 31(2), 158-175. doi:10.1086/668109
Tomlin, P. (2017). Beyond the monograph? Transformations in scholarly communication and their impact on art librarianship. In The Handbook of Art and Design Librarianship (2nd ed., pp. 213-224). Chicago, IL: ALA Neal-Schuman.