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If everything is a network, nothing is a network

Posted on by Brandon Klein

Only some of our proposed solutions for visualising the Waze traffic flows were ever put to the test. There’s only so much you can visualise when you want the driver’s eyes on the road rather than on the screen, interpreting nuanced network visualisations. But the trend towards self-driving cars, led by Waze’s new owner, aims to take the human factor out of the equation completely.

While the question of whether humans should drive their own cars is up for debate, I would strongly argue against the wider trend driving us away from our agency in relation to technology at large. It is quite mind-boggling to think that network algorithms do not see points connected by lines, while we cannot even imagine networks without them. As abstract, rudimentary and confusing as they may be, networks are an essential construct of our 21st century lives and we need the conceptual and technological tools to be able to analyse them.

Once we acknowledge the anatomy of the network as more than the formation of nodes and edges and their layout, we can use them carefully, bearing in mind that:

    Not emphasising the visualisation of the flow implies that only the layout of nodes and edges is enough to tell the whole story.
    By presenting a finite inventory of nodes and edges, we might be implying that what’s presented in front of us is the full network and no other nodes or links are involved.
    A network is an extremely flexible and abstract model, and wandering through its nodes and edges might quickly lead you in circles, following dead-ends or developing dubious conspiracy theories. Handle with care.
    Networks need narrative, both as a layer of annotation and as a way to present exemplary network flow.
    Directionality is important and can be a useful way to lay out the flow and even the protocol of some networks.
    Time is an organising principle in our lives and could sometimes serve a similar role in the visual representation of a network.
    Algorithm visualisation is the next frontier in network diagrams and for data visualisation at large. This is a call for humanistic agency in complex systems.

 

Finally, before we rush to join the dots and think of everything in terms of networks, we should really ask what makes a network model necessary in this case? Do we want to examine the relationships of the nodes? To compare the capacity of the edges? Can we really analyse the intricacies of the flows? And are we able to analyse the network’s protocols? And if we can, can we affect them?

If everything is a network, nothing is a network. But if this thing is a network, this is why you should care.