Digital Humanities
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“The Shape of History: Reimagine 19th Century Data Visualization” by Lauren Klein at Columbia University

originalpeabody

Professor Lauren Klein of Georgia Institute of Technology conducted a talk on “The Shape of History: Reimagine 19th Century Data Visualization.” In her lecture she examines the history of data visualization through various visualization pioneers specifically Elizabeth Peabody (1804-1894) and William Playfair (1759-1832). Professor Klein aimed to display how concepts from the past that were considered unusable, can help us better understand the visualization data of the present.

Professor Klein opened the lecture by displaying the “mural chart”, an image of the significant historical events of the seventeenth century of the United States. The image was created and designed by Elizabeth P. Peabody and displayed in her textbook, A Chronological History of the United States. Peabody’s visualization used a 10×10 grid overlaid with squares and colors to represent historical events. Each box is subdivided to represent various type of historical event, such as wars, battles, sieges, conquests, unions, losses, and divisions. Each nation is given it’s own unique color; the U.S. is orange, Spain is red and so forth. Peabody aimed to use the mural chart to “appeal to the senses directly, to provide ‘outlines to the eye’.” In hopes, that the students would convey their own narrative of history and reproduce historical knowledge. Peabody’s work is credited to be abstract and considered a failure for visualization due to its lack of clarity.

templeoftime

As Klein continued with her discussion she demonstrated the works of Emma Willard and Joseph Priestley. Emma Willard’s Temple of Time (1846) similar in structure to Peabody’s work is considered to be a heavily compressed visual. Willard’s visualization of the pantheon is a heavy decorated timeline of history, where each column represents one century. The image eschews clarity and is considered hard to decipher. Along with Joseph Priestley work, A New Chart of History (1769), which is also a heavily decorated timeline of history. Priestley’s visualization chart represents the geographical world in terms of who ruled/reigned and when. The similarities between Emma Willard, Joseph Priestley and Elizabeth Peabody’s work is the lack of understanding of the images during the period of creation. William Playfair is the last visualization pioneer Klein discusses. Playfair is credited with inventing the pie chart and bar graph. Playfair work The Commercial and Political Atlas 3rd (1801) is credited with being clear, informative and easy to understand. Playfair was driven to the invention of the bar chart because of the lack of data. He wanted to demonstrate the imports and exports of different countries and that was the logical way of visually displaying the information. Playfair’s work has served as a standard for digital humanists creating and using data visualization in their work.1786_playfair_-_exports_and_imports_of_scotland_to_and_from_different_parts_for_one_year_from_christmas_1780_to_christmas_1781

In Klein’s lecture she distinguish the differences between the works of Peabody and Playfair. Peabody’s work is considered as noted before more abstract, it allows the viewer or students to make their own interpretation of the visual data. Peabody, Priestley and Willard each challenge the norm of data visualization. Their works are or can be considered as failures in data visualization, due to the methods and perspective of the images. These images are only considered failures because they do not display or outline the data clearly. Klein challenges this notation she argues that we can learn from them. We can learn to use these methods to help create new narratives and interpretations. It can open the door to alternative modes of display, along with different ways of designing data visualization and new digital platforms for creating visualization.

After Klein demonstrates how the history of data visualization can convey ideas and help us better understand present data visualization, she moves on to discuss her work. The Digitization of Elizabeth Peabody’s Visualization Work Project allows users to create and interact with Peabody’s charts. The project is broken down into three modes: view mode, building mode, and compare mode. Each mode provides the users with a different perspective of Peabody’s charts. The viewing mode allows the user to interact with the charts. After becoming familiar with Peabody’s charts the individual is allowed to create their own. The compare mode displays two alternative visual forms of the charts and lists the elements in html code that represents the data. Klein then discusses the next step in her work, which involves bringing a physical computing project into the world. Klein goes into detail on how she’s managed to create such an object, and the long and tedious work that goes into it. The interface is designed to be setup like a quilt in which the individual squares will be lined with adjustable LEDs strips to light upon touch. To eventually be able to display various possibilities of colors the chart can pertain.

Professor Klein talk on the history of data visualization has help me better understand the different forms of visually displaying data. In Lothar Krempel article “Network Visualization” he discusses the various forms and methods of displaying data. In my understanding the presentation of data is important; color, shape, lines, nodes, symbols and sizes all contribute to successfully displaying data. Though from Klein’s talk I have gather that not all data needs to be presented in a clear concise manner, it can be left open for interpretation. These historical forms of data visualization can help us better comprehend present forms of data visualization and methods of display.

Work Cited:

[1] “Speculative Designs.” DH Lab. N.p., n.d. Web. 30 Nov. 2016.

[2] March 16, 2016 · by Erica Pramer · in Peabodyvis, Process. “The Digitization of Elizabeth Peabody’s Visualization Work.” DH Lab. N.p., n.d. Web. 30 Nov. 2016.

[3] Krempel, Lothar. “Network Visualization.” Network Visualization. N.p., n.d. Web. 30 Nov. 2016.