gence in circumscribed, cooperative roles to aid human observers in organizing, selecting, managing, and interpreting data. CHARACTERIZATIONS OF DATA OVERLOAD Data overload is the problem of our age -- generic yet surprisingly resistant to different avenues of attack. In order to make progress on innovating solutions to data overload in a particular setting, we need to identify the root issues that make data overload a challenging problem everywhere and to understand why proposed solutions have broken down or produced limited success in operational settings. There are three basic ways that the data overload problem has been characterized (Woods, Patterson, and Roth, 1998): 1. As a clutter problem where there is too much data: therefore, we can solve data overload by reducing the number of data units that are displayed. This has not proven to be a fruitful direction in solving data overload because it misrepresents the design problem, is based on erroneous assumptions a

“It is,..., the fundamental principle of cognition that the universal can be perceived only in the particular, while the particular can be thought of only in reference to the universal ” (Cassirer, 1953, p. 86).

McGuirl et al. Real-time feedback for crisis management decision-making Seeing is believing?: The effects of real-time, imagebased feedback on emergency management decisionmaking