Data Visualization: Resources for Teaching, Learning, and Research

an example of a data visualization created in Gephi, a third-party application supported by Academic Technology for FASData visualization, the presentation of data in a visual (pictorial, graphical, or other) format, can provide access to analytic trends and concepts in numeric, temporal, gospatial, or textual data that may otherwise be difficult to spot.

Common tools used for data visualization include R and Python, third-party applications like Tableau, Gephi, and Voyant Tools, JavaScript libraries like D3 and temporal, geospatial, and exhibition tools like Omeka, StoryMap, Timeline.js, WorldMap, and Carto. Resources for data visualization and data science training and assistance are available from several organizations around campus, including (but not limited to) Academic Technology for FAS, the Harvard Library, Research Computing in the Arts and Humanities, and the Institute for Quantitative Social Science.

Access to a suite of visualization applications, and to assistance with data visualization, is available on computers in the Multimedia Lab at Lamont Library, while workshops on approaches and tools used for effective visualization are frequently offered to faculty, staff, teaching fellows, and students by a combination of groups on campus. For more information on the digital toolkit or on visualization resources in general, please contact AT-FAS at atg@fas.harvard.edu.

Workshop Example

The following is an excerpt from a Harvard Gazette article about the two-day workshop "Thinking With Your Eyes: Visualizing the Arts, Humanities, and Sciences," held in February 2014 and sponsored by the interdisciplinary Digital Futures Consortium:

It seems like big data is everywhere you look. And in a way, it is: Maps, medical scans, and weather charts are commonplace forms of data visualization. Each was examined during “Thinking with Your Eyes,” a two-day conference that brought together experts in the arts, sciences, humanities, and technology — as well as academic and computing groups from across Harvard — to investigate how graphic representation brings knowledge to life.

“In a technological age where large amounts of data can be captured like never before, how big data is used and portrayed presents significant challenges,” said keynote speaker Martin Wattenberg, who along with Fernanda Viégas leads Google’s “Big Picture” visualization research group.

As presenters acknowledged the long and cross-cultural history of visual representation, it was often in the context of seeking new ways to make information more memorable.

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Faculty Research Examples
(provided by Research Computing in the Arts and Humanities)

Steven Clancy, Senior Lecturer on Slavic Languages and Literatures / Director of the Slavic Language Program

Russian Modules is a Russian language textbook currently under development. It makes use of the Neo4j graph database to support the visualization of Russian lemmas, both within context and in isolation. Additional functionality comes from D3js, a data visualization library that displays words within the database in the form of a series of force layouts. The goal of the project is to tie the graph database into the entirety of the book in order to create a unique interactive environment for learning. This involves the ability to highlight terms, explore meanings, noun declensions, and verb conjugations. In addition, this will allow for curriculum planning by analysing Russian language texts for their difficulty (as assigned by Steven and his colleagues). Copying and pasting text into the text analysis tool will highlight words based on word difficulty as it appears in the larger Russian language curriculum.

Malika Zeghal, Prince Alwaleed Bin Talal Professor in Contemporary Islamic Thought and Life in the Department of Near Eastern Languages and Civilization

Malika Zeghal is the principal investigator for Afkar, the Arabic word for ideas. Her project endeavors to trace Muslim intellectual networks during the interwar period of the early twentieth century. The research team began by parsing the content of various religious journals in the Middle East, beginning in Cairo, but expanding outward as far as Paris and the Philippines. This information will be used to create a dynamic world map that will display the provenance and movement of fatwa requests included in the journals. The goal is to display the various paths of knowledge contained within each of the journals, and to begin asking questions about the various imaginary networks (e.g. transcontinental intellectual communities) that existed at the time.

Research Visualization Example: Visualisation des Billets Vendus

Based on the research of Pannill Camp, Associate Professor of Drama at Washington University at St. Louis, Juliette Cherbuliez, Associate Professor of French at the University of Minnesota, and Derek Miller, Assistant Professor of English at Harvard University, Visualisation des Billets Vendus is a data interactive created by Christophe Schuwey, Lecturer at Université de Fribourg (Switzerland), and Christopher Morse, Senior Research Computing Specialist with Harvard's Research Computing in the Arts and Humanities group that reveals ticket sales at performances during the 1784-1785 season at the Odéon-Théâtre de l’Europe in Paris. 

Visualisation des Billets Vendus, while still in its early stages, has been an interesting thought experiment in theater representation and history, and presents a number of unique challenges. For example, how should one visualize a theater? Does it suffice to abstract a theater into shapes like a seating chart one might see on a website like Ticketmaster? What can be learned (or not) by specificity, that is to say, by attempting to recreate each individual seating area, or even each seat? Moving forward, the visualization seeks to encompass the entirety of the Comédie-Française registers collection, totaling over one hundred years of ticket sales, and various user interface improvements over time will make it easier for users to work with the heat map in more detail.