Representing The World
There is order and hierarchy everywhere. As far as we know, it started with Aristotle — his concept of ontology classified everything in the world into binaries: material or immaterial, living or non-living, human or animal. This classification system soon morphed into categorical branches on ‘Porphyrian trees’, which elucidates a myriad of things from morality to consanguinity or genealogy, Manuel Lima explains in his TED talk. A data visualization researcher, Lima takes us through the history of information and its visualization.
In the past decade, however, trees have been increasingly replaced by networks as the most popular metaphor used. For example, rather than displaying information about ecological systems in hierarchical trees of alpha predators, omnivores, herbivores, and plants, networks can be used to visualize the dynamic and complex nature of a particular biocommunity. Likewise, the same network model can be used to visualize gene relationships and social networks.
However, Lima does not expand on why networks have become the new information metaphor — at least beyond the obvious reason of businesses and organizations wanting to mimic trendy, sophisticated paradigms. Instead, I wonder if this shift represents a fundamental change in our relationships and organizational structures. For example, instead of a linear top-down (and tree-like) relationship from CEO to Vice Presidents to department heads to individual staff, is it possible that the organizations of today are more complex? That is, in addition to their direct supervisor, individual staff members may now be directly connected to someone “higher up the ladder” or in a different department (more collaboration?). Likewise, perhaps with more friendships now transcending traditional geographic, ethnic, and cultural boundaries, networks become the more appropriate method of complex social connections.
It is quite possible that this shift from linear relationships to complex web-like relationships is due to phenomena like Strong Triadic Closure. For example, imagine a marketing director who has strong ties to a) his subordinate (a marketing associate) and b) his colleague, the production director. The marketing associate will likely have to rely on information provided by the production director to create a draft advertising campaign; thus, as the strong triadic closure property predicts, at least a weak tie will form between the two. Of course, this form of information cannot be represented by linear, tree-like visualizations.
Thus, as we progress to a more open, collaborative society and economy, we will likely see an increasing reliance on network metaphors.