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Time/Data/Visualisation

Time/Data/Visualisation

MoMA on GitHub

The Museum of Modern Art has followed in the footsteps of Tate and Cooper Hewitt and published their collections data on GitHub.

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As I’m currently in the final phase of my PhD, I have to dedicate more time to writing and less to doing. Even so I can’t let MoMA’s datasets go by unnoticed.

The above screenshot is from a timeline tool I developed for visually analysing large cultural collections. I imported the MoMA dataset and visualised the object records along their production dates. We can see the timeframe the collection spans, with earliest pieces from the late 1700s and – obviously – a focus on twentieth century and contemporary items.

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The block shape around 1820 and the rectangular spike at 1900 represent large numbers of items that have the same, or very similar, production dates. Such anomalies can stand for series of items in the collection, they can be traces of curatorial decisions in cataloguing, they could be mistakes in dating, etc.

I inspected a few records in the 1900 spike and encountered a few photographs, which gave me the idea that the spike could represent a larger series of photographs – this would explain the high production output in a short timeframe. The tool allows me to colour records according to a field value, so I gave it a try and coloured all photographs in green:

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Uncertain times need uncertain measures

Data visualisations should represent their underlying data as accurate as possible, and timelines are no exception. However in many cases, temporal data is not accurate in the first place, as it can not easily be measured or counted. In order to represent such uncertain data accurately, we have to allow for ambiguousness in the visual representation of it.



Friedrich Strass’s Strom der Zeiten (1849, left) draws the world’s history as a fluid stream of empires in and out of each other, while Edward Lee’s History’s Largest Empires (2011, right) represents them as solid, discrete entities.

A visualisation should make understandable through an image, what is difficult to grasp in words, and enable new discoveries through visual analysis. Data visualisation in particular enables abstract numbers to be compared visually, or patterns to emerge from what might be just a list of measurements. It is always a translation, a representation of information in a graphical format, which by itself does not contain any new information in the strict sense 1 that was not contained in the raw data already. In the first instance, it makes existing information accessible for visual exploration.

Joseph Priestly stresses this aspect of his work in his Description of a Chart of Biography[1]. The text accompanies what can be considered one of the first graphical timelines (after the pioneering work by Jacques Barbeau-Dubourg): A chart depicting the lives of about two thousand individuals, represented by lines on a linear scale of years ranging from 1200 to 1800.

It is of course an understatement when Priestley declares himself simply “to be an assistant to the great Historians, Chronologers, and Biographers” (p.4), whose work forms the foundation of his timeline. What he means, is that he did not himself produce any new knowledge, but assembled the research of others in one coherent visualisation — laborious and painstakingly of course. In reward for his undertaking, he was now able to see and also show to others, the relation and succession of historic figures, their contemporaries with whom they might have conversed, and the periods when cultural life flourished or, symbolised by emptiness, stalled. The representation of chronological information in graphical form opened it up for visual analysis and exploration, which enables new hypotheses to be developed from which ultimately new knowledge can be gained.

I mention this historic example of a graphical timeline, because it exhibits awareness for key requirements a timeline needs to fulfil, which are still relevant today. Being one of the first to ever create a timeline, Priestley gave careful consideration to all of his design decisions, which he documented in his Description.

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[1] J Priestley, A Description of a Chart of Biography, 1764

Notes:

  1. According to Shannon’s Theory of Information