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What if data visualized itself?

How nature organizes hidden layers of information

Image by author
Image by author

"In this complex and multidimensional data environment, the role of visualization will be key in providing the capacity to recognize the emergent patterns and processes of these [natural] phenomena. Visualization will itself become organic, as it will need to adapt to simulate information from a wide spectrum of sources, ranging from micro/organic to macro/planetary states."[1]

In adopting computational and algorithmic design methods into contemporary design practices, the computer has become a medium capable of translating designers’ logic into computational logic and thereby automating abstractions. Examples of such applications include generative typographic systems and parametric architectural practices, where form is specified by an adaptive and modular range of values in parameters, variables that define themselves by incoming fluxes of data. Computation allows for the automation of rules and real-time generation of forms in response to this data, thereby challenging previously held distinctions between process and product in many cases.

Generated abstractions allow designers to transcend arbitrary social conventions of form. Using models that mimic complex systems leads to the creation of patterns that emerge as a result of naturally occurring processes beyond the influence of culture and society. Generative processes help us understand the world, and remind us that the universe itself is a generative system, ever-changing and kaleidoscopic. It would, therefore, make sense to look unto nature for not just descriptive, but also organizational inspiration.

"In our zealous desire for familiar models of explanation, we risk not noticing the discrepancies between our own predispositions and the range of possibilities inherent in natural phenomena."[2]


Nature seems to leave behind evidence of its efforts, to which we are witnesses, oblivious to the fact that every pattern is a mere snapshot of much longer operation in motion, one of information exchange.

Credits: leagun at FreeImages
Credits: leagun at FreeImages

The passage of time is recorded, for example, by trees who gain a new protective sheath annually. The cross-section of a tree reveals these layers of data in the form of growth rings, which arise due to the change in the speed of growth through the four seasons. Tree rings are more visually pronounced in environments that have a distinct hot and cold season. Typically one ring records the passage of one year in the life of the tree. The width of the ring is directly proportional to how wet the particular year was. Therefore an older tree’s growth rings can tell us about ancient climate, and tree rings from different continents can be compared to infer different climatic conditions. Similar annual growth rings can be seen on certain shells and corals as well.

To an information designer, this dendrochronological (dendron = tree, Chronos = time, logos = the science of) phenomena could be seen as a data visualization because:

  1. It communicates a quantitative message visually or experientially i.e. the age of the tree, climatic conditions of the location, etc.
  2. It has abstracted information in some schematic form, including attributes or variables for the units of information i.e. the number of rings, the width of the rings, etc.

Nature with its regenerative capabilities seems to possess an intelligence analogous to some generative art and design practices. The role that trees play in this regard is as data-collecting cultural probes, that not only contain but also communicate the imprints left on them, through the complex interactions with their environments.

Similarly, a stack of tomatoes or strawberries for instance, although similar in shape, indicate ripeness through its observable features. They could be placed on a visual spectrum, in this case from hard to soft, or green to red. As a result of their identical shape, the information container is ignored and the content inside comes to focus. Comparing one tomato to another in such a way brings to mind a visualization technique called ‘small multiples’, popularized by Edward Tufte. Small multiples refer to many graphs of the same scale and axes, placed next to each other thus making them easy to compare with one another.

(Left- Rod Miles at FreeImages) (Right-Simone Dalmeri at Unsplash) Hydrangea flowers range from blue to pink depending on the type of soil they grow in, directly mapped to its pH levels.
(Left- Rod Miles at FreeImages) (Right-Simone Dalmeri at Unsplash) Hydrangea flowers range from blue to pink depending on the type of soil they grow in, directly mapped to its pH levels.
(Left-Adam Nieścioruk at Unsplash) The colour and texture of some Lichen varieties is indicative of levels of air pollution (Right-Image by author) These pencils look awfully similar to a histogram.
(Left-Adam Nieścioruk at Unsplash) The colour and texture of some Lichen varieties is indicative of levels of air pollution (Right-Image by author) These pencils look awfully similar to a histogram.

Such examples are self-contained systems in themselves, which provide us ways to inquire how information may be visualized automatically as it is being exchanged, without the need for extrinsic intervention. As I came about this idea, I soon discovered that a similar topic had already been theorized by Dietmar Offenhuber known as ‘Autographic’ or ‘Indexical Visualisation’. Autographic Visualisation certainly reimagines thinking of data in terms of its physicality and material processes and it outlines clear methodologies to do so. Rather than abstracting data into metaphors, the traces that are left behind by objects become the visualization.

Autographic vis is also rooted in Charles Sanders Peirce’s semiology, which defines indexicality as "a causal connection between an object and its effects in the real world: dyed bacterial cultures in a petri dish, the chemical signatures of pollutants in the environment, the wear on the pages of a book. Indexicality connects the abstract domain of information with bodily experience."[3] They are, however, often signifiers of feedback loops, and not of entire systems themselves. On the other hand, the examples I mention, propose directing the autographic methodology toward a systems framework. As Tufte theorized the maximization of ‘data-ink’, this organic process speculates a maximization of ‘data-energy’. Data neither arises nor is visualized from a centralized location but instead emerges over time from the interactions of many causal loops. Such an approach to the discourse on Big data could possibly reduce the monopolization of information in the hands of a few tech giants.


Domestic Data streamers, a data visualization studio, applies this technique to the way they communicate information. Their projects often use human beings as a means to generate collective and participatory data visualization experiences, which may take the form of a digitally-mediated physical environment. In taking graphs and charts out of their familiar digital context and placing them in these unique physical settings, the information takes on a sculptural or object-oriented configuration. People are also more likely to share their stories, once they’ve experienced it outside of the "personal sphere" of a personal computer, where they can compare different tangible values with greater ease.

In a project called Mood Test, for example, they establish only a simple set of rules, that the data would be physically colour-coded by individual contributors. The emergent visualization is a burgeoning map of demographic narratives which can be easily read, while still retaining its Complexity. The data as well as its abstraction, only materialize out of people’s participation. With each interaction, the piece imbibes more gradation, and at some point crosses a threshold from process to an actual product that can be called a visualization. Nonetheless, it does not stop being a process even after that point.

It could be described as a data language in a space, as opposed to a chart. This idea of a data space remains unexplored, wherein a graph may be placed in the physical or digital world so that it reveals itself spatially and temporally. The information appears only when people realize where and how they would like to be situated within the controlled environment, and the visualization is unique to that specific location and section of participants. In a different context, the artwork would emerge differently, thereby demonstrating themes of modularity and impermanence. Such projects beg the question- must the role of a data generator and data designer be mutually exclusive?

Information researcher Wesley Willet imagines how autonomous agents could be employed by the year 2033, to capture and visualize complex patterns in real-time, thereby quite literally mimicking nature. His vision takes the form of ‘Cetonia scarabs’ that can be deployed to assemble into drone swarms. Each mechanical insect is equipped with embedded cameras and sensors, and can apparently survey, compute and record almost anything. The cluster is also said to be able to coordinate internally to form interactive charts, graphs, and visual diagrams to reveal data.

When done properly, this decentralized design process can be a way to visualize diversity and granularity, which can otherwise be difficult to do. It could also reduce the labor involved in visualizing complex unfathomable matters like the internet, cryptocurrencies, or other forms of hypertext.

"A graphic does not distort if the visual representation of the data is consistent with the numerical representation. What then is the ‘visual representation’ of the data? As physically measured on the surface of the graphic? Or the perceived visual effect? How do we know the visual image represents the underlying numbers?"[4]

More examples I collect: https://in.pinterest.com/vivekm2/self-visualising-information/


Citations:

[1] Lima, Manuel, Visual Complexity: Mapping Patterns of Information (New York: Princeton Architectural Press, 2011)

[2] Keller(1985) in Mitchel Resnick, Learning about Life (The Media Laboratory, MIT, Cam- bridge: Published in Artificial Life, vol. 1, no. 1–2, spring 1994) https://web.media.mit.edu/~mres/papers/ALife/ALife.html

[3] Offenhuber, Dietmar & Orkan Telhan, Indexical Visualization – the Data-Less Information Display (2015)

[4] Tufte, Edward R. The visual display of quantitative information (Cheshire: Graphics Press, 1983)

Other references:

Anderson, Mally, Exploring Decentralization: Blockchain Technology and Complex Coordination, Journal of Design and Science (MIT Press, February 2019) https://jods.mitpress.mit.edu/pub/7vxemtm3 (accessed 20 May 2019)

Bollmer, Grant David, Theorizing Digital Cultures (New York: Sage Publications Ltd; 1 edition, 2018)

Bratton, Benjamin, The Stack: On Software and Sovereignty (London: The MIT Press, 2016)

Bratton, Benjamin, ‘Some Trace Effects of the Post- Anthropocene: On Accelerationist Geopolitical Aesthetics’, e-flux, 46 (2013) [https://www.e-flux.com/journal/46/60076/some-trace-effects– of-the-postanthropocene-on-accelerationist- geopolitical-aesthetics/](https://www.e-flux.com/journal/46/60076/some-trace-effects– of-the-postanthropocene-on-accelerationist- geopolitical-aesthetics/) (accessed 19 June 2019)

Burnett, Kathleen, ‘Toward a Theory of Hypertextual Design’ (Postmodern Culture 3.2, January 1993) http://pmc.iath.virginia.edu/text-only/issue.193/burnett.193 (accessed June 19, 2019)

Dragicevic, Pierre & Yvonne Jansen ‘List of Physical Visualizations’ (2012), http://www.dataphys.org/list (accessed 6 July 2019)

Galanter, Philip & Ellen K. Levy, Complexity (Leonardo, vol. 36, no. 4, 2003) pp. 259–267, JSTOR www.jstor.org/stable/1577312

Galanter, Philip, What is generative art? Complexity theory as a context for art theory (6th Generative Art Conference, 2003)

Hanrahan, Pat, ‘Self-Illustrating Phenomena’ (Stanford Graphics, November 2004) http://www.graphics.stanford.edu/~hanrahan/talks/selfillustrating/ (accessed 28 June 2019)

_Offenhuber, Dietmar, ‘Autographic Visualization – Talk at Google Cambridge / BostonCHI’ (March 2019) https://www.youtube.com/watch?v=4_YNpx1R8i8 (accessed 28 June 2019)_

Tufte, Edward R. Envisioning Information (Cheshire: Graphics Press, 1990)

Waldrop, M. Mitchell, Complexity: The Emerging Science at the Edge of Order and Chaos (New York: Simon and Schuster, 1992)

Wiener, Norbert, The Human Use of Human Beings: Cybernetics and Society (London: Free Association Books, 1989)


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