Searching for Meaning in Complex Databases: An Ecological Perspective

ion attacks complexity by introducing conceptual structures. For example, the “gist” of a story could be preserved even though all the parts (words) were changed. In this sense, the “gist” is an abstraction. Another example is categorization. A category such as “furniture” reflects a relation among objects that cannot be reduced to a list of common parts. Abstractions generally function to highlight dimensions that are thought to be “essential,” while blurring other dimensions that are considered less important. Abstraction is illustrated very clearly in Hutchins (1995) discussion of different forms of maps. Maps are not simple iconic images of the layout of the earth. Rather they are carefully crafted abstractions designed to highlight some dimensions (e.g., line of sight directions) at the cost of blurring others (e.g., area). Rasmussen (1986) reminds us that we need both strategies and that the strategies are not independent. The dimensions highlighted and blurred by the abstraction process have implications for what decompositions will be appropriate. Figure 4 attempts to illustrate this interaction between abstraction and decomposition. Abstraction is illustrated as the vertical dimension of this space and level of decomposition is illustrated as the horizontal dimension. Although five levels of abstraction are represented in Figure 4, consistent with Rasmussen’s (e.g., 1986) Abstraction Hierarchy, we will not attempt to define these levels or to make any claim about the absolute value of these particular levels. The claim that we do want to make here is that no single level of abstraction provides a comprehensive survey of the meaning landscape. Abstractions that highlight the dimensions associated with satisfying (e.g., intentions and consequences) often will blur the dimensions associated with affording or specifying and vice versa. The diagonal regions of the matrix highlighted in Figure 4 reflect experiences from previous work analyses and from protocols of experts during problem solving in their domain (Rasmussen, 1986; Rasmussen et al. 1994; Vicente, 1999). These experiences suggest that questions associated with “why” (satisfying) are typically best seen with high degrees of abstraction and relatively gross levels of decomposition. This reflects a “top-down” view of work. Questions associated with “how” (affording and specifying) typically require more concrete descriptions and finer levels of decomposition. This reflects a “bottom-up” view of work. The “bottom-up” view helps to answer questions about how to carry out a particular procedure. The “top-down” view, however, becomes critical for deciding which of two procedures might be best in a given context. Solving the adaptive control problem typically requires iterating between the “bottom-up” view and the “top-down” view. The bottom-up view helps to clarify the best way to carry out a particular strategy. The top-down view is useful for evaluating different strategies to assess which of several strategies might be most appropriate for a given context. Historically, the entry of CSE into many work domains has been a controversy over different possible strategies or over the appropriate criterion for switching from one strategy to another. This reflects the realization that there may be more than one “best way” and that the best way may vary with the changing context.