Woods, D. D.

Abstract: Data overload is a generic and tremendously difficult problem that has only grown with each new wave of technological capabilities. As a generic and persistent problem, three observations are in need of explanation: Why is data overload so difficult to address? Why has each wave of technology exacerbated, rather than resolved, data overload? How are people, as adaptive responsible agents in context, able to cope with the challenge of data overload? In this paper, first we examine three different characterisations that have been offered to capture the nature of the data overload problem and how they lead to different proposed solutions. As a result, we propose that (a) data overload is difficult because of the context sensitivity problem – meaning lies, not in data, but in relationships of data to interests and expectations and (b) new waves of technology exacerbate data overload when they ignore or try to finesse context sensitivity. The paper then summarises the mechanisms of human perception and cognition that enable people to focus on the relevant subset of the available data despite the fact that what is interesting depends on context. By focusing attention on the root issues that make data overload a difficult problem and on people’s fundamental competence, we have identified a set of constraints that all potential solutions must meet. Notable among these constraints is the idea that organisation precedes selectivity. These constraints point toward regions of the solution space that have been little explored. In order to place data in context, designers need to display data in a conceptual space that depicts the relationships, events and contrasts that are informative in a field of practice.

  This article is not yet tagged

Checkout More Details | Available Online