The Horizon Report on Visual Data Analysis

Check out the new Horizon Report (click here).


Each year, the report identifies emerging technologies or practices that are on the academic horizon (within one year, reported upon here, but also on the horizon)...but it also addresses key, technology-related trends that impact our work.

I have excerpted commentary on visual data analysis here, but do check out the full report if you need to procrastinate while doing "class prep" for the new semester.........and think about how this could help our social work visual learners..............

Visual Data Analysis


Time-to-Adoption Horizon: Four to Five Years

Visual data analysis blends highly advanced computational methods with sophisticated graphics engines to tap the extraordinary ability of humans to see patterns and structure in even the most complex visual presentations.  Currently applied to massive, heterogeneous, and dynamic datasets, such as those generated in studies of astrophysical, fluidic, biological, and other complex processes, the techniques have become sophisticated enough to allow the interactive manipulation of variables in real time. Ultra high-resolution displays allow teams of researchers to zoom in to examine specific aspects of the renderings, or to navigate along interesting visual pathways, following their intuitions and even hunches to see where they may lead. New research is now beginning to apply these sorts of tools to the social sciences and humanities as well, and the techniques offer considerable promise in helping us understand complex social processes like learning, political and organizational change, and the diffusion of knowledge

Relevance for Teaching, Learning, or Creative Inquiry:

As stated previously, one of the most compellingaspects of visual data analysis is in the ways it
augments the natural abilities humans have to seek and find patterns in what they see. By manipulating variables, or simply seeing them change over time (as Gapminder has done so famously) if patterns
exist (or if they don’t), that fact is easily discoverable.Such tools have applicability in nearly every field.
As the tools, their capabilities, and their variety continue to expand, their use is already making its
way out of scientific and engineering labs and into business and social research. Creative inquiry is
benefiting from a wide range of new tools that are exposing trends and relationships among both
qualitative and quantitative variables in real time, and making longitudinal relationships easier to find and
interpret than ever. Textual analysis is an area that tools like Wordle have revealed as especially suited

to visual techniques. The promise for teaching and learning is further afield, but because of the intuitive ways in which it can expose intricate relationships to even the uninitiated, there is tremendous opportunity to integrate visual data analysis into undergraduate research, even in survey courses. Models of complex processes in quantum physics, organic chemistry, medicine, or economics are just a few of the ways in which the outcomes of visual data analysis can be applied to learning situations.

Visual data analysis may help expand our understanding of learning itself. Learning is one
of the most complex of social processes, with a myriad of variables interacting in ways that are not
well understood, making it an ideal focus for the search for patterns. Related to this is the opportunity
to understand the variables influencing informal learning and the social networking processes at
work in the formation of learning communities. The tools for such analyses exist today; what is needed
are ways to balance privacy with the kinds of data capture that can inform such work.