2010 Horizon.museum Short List

2010 Horizon.museum Report Short List pdf

Time-to-Adoption Horizon: One Year or Less

Time-to-Adoption Horizon: Two to Three Years

Time-to-Adoption Horizon: Four to Five Years

Critical Challenges

Key Trends


Visual Data Analysis

Time-to-Adoption: 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 into interesting 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 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 Museum Education and Interpretation

  • The applications of visual data analysis for science museums are myriad, and can expose visitors to the emerging science made possible by extremely large data sets, such as those found in studies of climate, astrophysical, or geological processes. The ability of these tools to represent changing dynamics in these processes visually is also an opportunity to highlight the human brain enormous capacity for pattern matching.
  • Historical, art and other museums might use these tools to examine the effects of their own microclimates on the objects in their collections.
  • Visual data analysis could be a useful tool for curators to understand the nature of "gaps" in collecting areas and use them to tell stories about art history in local collections.

Examples


For Further Reading

FlowingData Graphs Your Life Via Twitter
http://www.fastcompany.com/blog/clay-dillow/culture-buffet/flowingdata-graphs-your-life-twitter
(Clay Dillow, Fast Company, 15 July 2009.) Track anything you like via a private Twitter address: every time you have a cup of coffee, blood sugar readings, chocolate cravings, workout time or distances. A graph builds over time of all the data sent in.

New Visualization Techniques Yield Star Formation Insights: Gravity Plays Larger Role Than Thought
http://www.sciencedaily.com/releases/2008/12/081231152305.htm
(Science Daily, 4 January 2009.) Early in 2009, a new computer algorithm developed at the Harvard Initiative in Innovative Computing demonstrated that data visualization is critical in the discovery of new information, not just in the final presentation of data.