Radial maps

1. Hereford map (c. 1300): Jerusalem at the centre of the circle
2. Borgia map (c. 1450): Babilonian, Alexandrian, Carthagian, and Roman empire a the centre (extremes of the world as monstruos races)

Cartographic maps

Europa Regina map (c. 1500)

Critical cartography:
modern maps not as an evolution, but a (visual) representation of power

Data about places (maps)

• Territory / census
• Extended geographical information: e.g. Google streetview in Germany

Data between places (flows)

• Extraterritoriality of data
  Eichenser, K. (2017, November 10). Data Extraterritoriality.
• Reformulation of concepts like "space, "territory", "population"
• E.g. https://www.submarinecablemap.com/ + https://traceroute-online.com

Which one of these is a familiar type of visual information representation?

1. Johannes Buno [the 400s] (1672)
2. William Playfair, Scotland's imports and exports 1780-1781 (1786)

Cartesian coordinates

The bivariate graph, with its inexhaustible capacity to spatialize parameters and put them into relation with each other, is an intellectual product of an era in which rationality could be at the service of theoretical and practical knowledge

Drucker, J. (2014). Graphesis: Visual Forms of Knowledge Production.

Charles Jospeh Minard, Napoleon's army across Russian Empire of Alexander I (1869)

John Snow data on the 1854 cholera outbreak in London

Informative visuals not only about visual data

• Everynoise

Every Noise at Once is an ongoing attempt at an algorithmically-generated, readability-adjusted scatter-plot of the musical genre-space, based on data tracked and analyzed for 5,597 genre-shaped distinctions by Spotify as of 2021-10-02. The calibration is fuzzy, but in general down is more organic, up is more mechanical and electric; left is denser and more atmospheric, right is spikier and bouncier.

• Hamilton

Visual cues open and constrained data

"In its most basic form, visualization is simply mapping data to geometry and color."
Yau, N. (2013). Data Points: Visualization That Means

See: Periodic table of visualisation methods

Data can always be represented differently

McInerny, G. (2018). Visualizing data: A view from design space.

While information may be infinite, the ways of structuring it are not (…) Your choice will be determined by the story you want to tell. Each way will permit a different understanding of the information—within each are many variations

Wurman, R. S. (2000). Information Anxiety

Interpretation includes affective elements

Peck, E. M., Ayuso, S. E., & El-Etr, O. (2019). Data is Personal: Attitudes and Perceptions of Data Visualization in Rural Pennsylvania.

You can listen a podcast about this study here

Data is often used to misrepresent information

Mona Chalabi

A critical visual use of data should consider the un/misrepresented populations

"the rendering of statistical information into graphical form gives it a simplicity and legibility that hides every aspect of the original interpretative framework on which the statistical data were constructed."
Drucker, J. (2011). Humanities approaches to graphical display></span

"When visualizing data, it might be inevitable that we hide some patterns as we reveal others. Patterns can be a composite of features that might be optimally revealed in different kinds of charts and not viewable in any single graph."
McInerny, G. (2018). Visualizing data: A view from design space, 136

Affective mapping:
https://guns.periscopic.com/
(from data feminism)

Design Space is envisaged as a hyper-volume of all possible visualization designs with as many dimensions as there are ways to visualize data using coordinate and mapping systems, visual encodings and formatting, scales and sizing, sampling and aggregation methods, etc.

McInerny, G. (2018). Visualizing data: A view from design space.

Beyond realists representations of data

• rethink graphical display according to humanistic principles
• a constructivist instead of a realist approach to data representation
• explicit representation of the subjective expression of perceived phenomena
• represent ambiguity and uncertainty

Drucker, J. (2011). Humanities approaches to graphical display>

Affective small data: Dear Data project

See also: Quantified selfie project and Drops (work-in-progress)