Deeptime

Deeptime is a P5.js-based navigable clock that arranges the user’s system time into a series of nested circles, much like gears, each representing a unit of time: from milliseconds, to a month, to a millennium. The project seeks to explore the interconnected, cyclical (i.e. nonlinear) nature of time, as well as time at scales that exceed human understanding (as in the case of geological or ‘deep time,’ a term coined by John McPhee from which this project gets it name). In allowing users to navigate (via pan-and-zoom) a visual representation of these cycles in relative scale to one another, Deeptime leverages Manovich’s ‘anti-sublime ideal in data art’ to manifest an embodied understanding of time from which we are increasingly estranged.

Click here to run Deeptime (not currently supported on mobile).

In his Hyperobjects: Philosophy and Ecology after the End of the World, Timothy Morton writes of how “1945 [signalled the beginnings of] the Great Acceleration, in which the geological transformation of Earth by humans increased by vivid orders of magnitude … This is not only a historical age but also a geological one.” The idea of time at a geological scale, expanded beyond the grasp of human comprehension, is sometimes referred to as ‘deep time,’ a term coined in the 1980s by John McPhee. The term was later adopted by Buddhist scholar and systems ecologist Joanna Macy, who writes:

The technologies and economic forces unleashed by the Industrial Growth Society radically alter our experience of time, subjecting us to frenetic speeds and severing our felt connection with past and future generations … Measure of time, once based on changing seasons and wheeling stars, then much later the ticking of the clock, is now parceled out in nanoseconds. We have lost time as a biologically measurable experience.

Joanna Macy and Molly Brown, Coming Back to Life: The Updated Guide to the Work That Reconnects (2014)

For such an essential component of human experience, time is perhaps one of the most taken-for-granted data streams with which we interact on a daily basis. As representations of time become increasingly digitized, its cyclical nature is likewise increasingly obfuscated: gears, pendulums, and turning hands give way to a direct (albeit meaning-laden) alphanumerical semiotics. In enhancing the underlying logic of this translation rather than seeking to obscure it, Deeptime exposes the complex interconnected system of temporal data that governs so much of embodied human experience. By pulling its data from the user’s system time (usually set automatically based on one’s location) and displaying this data in a navigable way (allowing one to pan and zoom between temporal units using a mouse wheel or trackpad), Deeptime invites reflection upon one’s position within these vast cycles and, perhaps, offers an opportunity to make fresh peace with the present: a moment in context, without beginning or end.

Like other Mortonian hyperobjects, time cannot be observed from a privileged exterior perspective: all attempts to describe it are made within its bounds, all experiences of it mere fragments of the whole (Morton 17). As such, representation matters: experimentation in representing temporal data is critical to refining and evolving our understanding of it. Building upon the lineage of works such as John Maeda and Michio Iwaki’s Line Java Calendar (1997) and Jussi Ängeslevä’s Last Clock (2002), Deeptime orients itself towards communicating the complex, ever-changing data stream of passing time as a recursive data object — one whose exploratory capacity and relative scaling might introduce new ways of understanding and accessing time, especially those more visceral / sublime than linguistic / rational. By allowing the user to expand or contract time, Deeptime is less about capturing all facets of the elusive present and more about clarifying the framework through which the present emerges; the micro- and macroscopic processes working in harmonic tandem to propel us into the future.

This project was designed for Professor David Bouchard‘s RTA842 Data as Material course and features additional code written by him.