Emo-Devo Landscapes: Animated Forms
iSAHIB Steps used data from the iSAHIB project to explore both between-person differences and multiple time-scales. From the visualizations and sonifications of them, we learned a lot about meaning, both in terms of person-level characteristics that are stable over a fast time-scale and change over slower time-scale and in terms of person-context relations – and how people people’s behavioral patterns (foreground elements) might changes in relation to the environment (background elements).
Using the same data archive we have also explored alternative visual representations of change in two (or more) dimensions (like the yellow and pink elements in “Steps”). Exchanging the “windows” for “spaces” provides access to surfaces or landscape-like images. What if the landscape is a person that is “shaped” by changes in the environment (earth, wind, & fire)?
In a recent paper (Ram et al, 2013) we described 3-d rendered images of multivariate density distributions as behavioral landscapes – and examined the possibility that those landscapes change as an individual transitions through life events. The landscape classification, we surmise, can be interpreted as (a) a description of the individual, (b) a description of the person’s environmental context (since he or she “lives” within the hills), or (c) a description of the person-context transactions. In each case, the landscape can be shaped by large external events (e.g., marriage, birth of a child, retirement, etc).
As such, it is of great interest to integrate the landscape forms generated from micro time-scale (daily) data with macro time-scale changes that occur over the life span. Since the archive includes data obtained from individual age 18 to 90 years, we could apply the landform classifications techniques to empirical data that covers an entire sample in order to construct and examine a (multi-person-based) landscape the “evolved” with age. That is we could so how the landscape transformed over the adult lifespan. Below is an animation through which we can see “erosion” of the landscape – the mountain decreases the area around the base as a notable feature of age-related change.
This representation of long-term (age) changes in behavioral landscapes (that are representation of daily experiences) has now become, in collaboration with the Life-span Development Laboratory at Stanford University, the basis for a follow-up paper examining age-related changes in emotional experiences. Check out the similarity of changes seen in the animation of data from their “Beeper Study” (Carstensen et al., 2011).
