Network Clouds and Relational Mappings

….”Space” is more complex and dynamic than previous formal models allowed.  Ideas about spatiality are moving away from physical objects and forms towards the variety of territorial, political, and psychological processes that flow through space.  The interrelationships amongst things in space, as well as the effects that are produced through such dynamic interactions, are becoming of greater significance for intervening in urban landscapes….”

The quote above is taken from James Corner’s influential essay The Agency of Mapping: Speculation, Critique and Invention written in 1999 (in Denis Cosgrove’s Mappings).   The writing served as a motivation to approach map making as a generative and speculative design activity that emphasized interrelationships and effects (Deleuze) rather than the production of inert, mimetic end products.  As great as Corner’s essay is, the examples cited are beginning to age, and recent posts by Polis and Serial Consign provide great updates to the potential agency of mapping a decade later.   I would like to continue this dialogue by focusing on (and perhaps advocating for) a certain type of contemporary mapping – the network.

Our last post reviewed Muir Webs as generative maps that reveal the inner workings of  past and present spaces – what might be considered the spatial, or macro variant of connectionism.

Eric Sanderson describes Muir webs as a new grammar for mapping habitats, analogous to language.  Well if so, can the diagram evolve, shift and fluctuate like languages and environments do?  Can it account for emergence? The more I look at the image (captivating due to the quality of the rendering, and perhaps because it leaves so much unexplained) the more I feel its stasis.  As Sanderson and his team continue to refine these webs (they seem to be early beta prototypes) can they become more dynamic in operation?  Taking Sanderson’s language metaphor a bit further and into the contemporary, can these relationships be read at nested scales, similar to visual thesaurus?

The recent publication Data Flow: Visualizing Information in Graphic Design,  contains a chapter on network maps similar to these, called Datanets:

“When individual data points develop tension and connection with each other, the resulting structure becomes an entity in its own right – the network.  It draws life essentially from connection and connectedness, and it is these qualities that are directed explicitly by the designer to show cause, context, or collaboration…the power of the network lies in elevating node to nexus, a humble contributor to a new level of meaning through association.”

And similar to the authors mentioned above, Data Flow’s introduction speaks of design agency as ‘patterns of intent’:  “the map maker “shapes an experience or view of the data with a particular aim in mind…it is the designer who makes this connection possible, by turning  his or her inspiration into a form that opens up new meaning.”

Network maps, or maps of association are particularly well suited to an understanding of systems and/or networked ecologies (whether they be landscape, industrial, institutional/corporate, natural, synthetic, urban, anthropogenic, etc.). As many streams of contemporary environmental and spatial design have come to emphasize systems and processes (…in addition to form), the need to better map and understand the relational qualities of these systems is paramount.  In contrast to modern formalism, the new horizon in spatial design must concern itself with visualizing formative structure and that which is largely invisible.   The contemporary spaces of flow (globalization and hypermobility), infrastructure, environmental crisis (global climate change,  loss of biodiversity, pollution and environmental degradation) and our advancements in understanding spatial processes (landscape ecology and resilience theory) beg for a more sophisticated understanding of what it means to tinker with space and systems.  As the Infranet Lab recently said on a post related to the (blindly) brave new world of  geoengineering

“The dropping of massive quantities of iron into the ocean and promoting large-scale phytoplankton production would have great repercussions on ocean ecosystems – repercussions that we cannot predict…The largest issue with attempting to orchestrate a climatic transformation is that we just don’t know enough about how our atmosphere works and the repercussions of our tampering.”

The agency of network maps may be the best way to test and better understand both existing environmental forces and the effects of proposed design interventions on those forces.

Similar to designing systems, the mapping of their inner workings is complicated and an exercise in Simplexity. The challenge of mapping the agency of systems lies in avoiding Borge’s 1:1 map fallacy, but in terms of complexity rather than size.  As the amount of variables and interconnections increases, the connective filaments appear more and more as a dense cloud rather than a network of interconnected nodes (note the black mass of relationships in the Muir Web.  As Sanderson increased the number of relationships by mapping individual species rather than groups, the extent of web cloud increases significantly).

Returning to the thought of creating a Muir Web for contemporary Manhattan, mapping the relational fabric of just a single human in NYC is a complex task, as Nicholas Feltron has demonstrated with his personal play off of the data mapping of corporate annual reports:

The constellation of people in Feltron’s personal network, followed below by where he goes, his methods of transport, and his grazing habitats.

Feltron is one person of the 1,620,800 or so people living on the island.  Imagine the conglomerate webbing of all the other inhabitants of new york, plus other systemic forces at work.

Or consider the odd micro spatial/visual network many of us inhabit for far too much of our time:

[Posted by cnverge design (and brought to our attention by Faslanyc) “This is a map of my activity on my computer screen @ work late this afternoon. Antoly Zenkov, an interactive artist & programmer, created an incredible freeware (IOGraph) that allows you to graphically track your mouse movement for any amount of time. Lines represent mouse paths, and dots connote periods of inactivity.” Check out Zenkov’s photostream here]

I like the mapping above because it reveals network connections, spatial relationships and the temporal dimension as interrelated variables.

Zooming way out from personal networks, remember the maps of the internet that were popular a few years ago?

[Map of one day of the internet (connections between routers) from the Opte project.]

The image above is incredibly similar to the Muir Web – abstractly relational but lacking spatial definition. In contrast, Chris Harrison’s map of internet connectivity highlights the spatial distribution of connectivity.

[Chris Harrison: “The Dimes Project provides several excellent data sets that describe the structure of the Internet. Using their most recent data at the time (Feb 2007), I created a set of visualizations that display how cities across the globe are interconnected (by router configuration and not physical backbone). In total, there are 89,344 connections.”].

[Global air travel connections, from the The Endless City (blue area is the U.S.)]

In both Harrison’s internet map and the mapping of international air travel connections () only spatial network connections are mapped, which imply, and give form to these territories.  Both maps reveal heightened connections as well as extensive disparities in globalization processes.

[Detail of international air travel showing Europe, Africa and Asia]

Digital Urban and Urban Tick (consistent researchers of mapping urban networks) have posted recent explorations mapping the ever-expanding chatter occurring in the Noosphere.

[London Twitter Cloud (from digital urban “The data covers a weekend period from Friday evening to Monday morning containing 380,000 individual tweets. Within these 60,000 were geo-referenced, tweeted by 5,500 individual users.”]

Their media meshwork of geo-referenced tweets, Google maps and animation/film is compelling, again because it integrates spacial relationships with time.  However, the mapping is still at the stage of being a dispersal graph, as we don’t know the relationships between the tweets other than their agglomeration in high density London. The tweets’ relationships and what they are responding to is bound up in a much more expansive and more nebulous network.

A similar question emerges when looking at the spatial distribution of corporate systems, such as the mapping of Starbucks in Portland Oregon shown below:

(If you haven’t already seen it, check out Flowing Data’s temporal mapping of the feral proliferation of Wal-Mart and Sam’s Club over the last 40+ years)


  1. Hi,

    It may be irrelevant!
    I would like to know is the first picture an image of neurons in brain?

    it is so important.

  2. Yes indeed – it’s an image of a neural network.

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