DAISY: A decision support design methodology for complex, experience-centered domains

Abstract

Users at different levels of domain experience have very different needs. For example, a system designed to assist domain novices may frustrate experts and vice-versa. This is one of several challenges specific to building decision support systems for experience-centered domains. Examples of experience-centered domains include medical diagnosis [37], chess [15], [16], as well as most professional design or planning tasks [24]. A second challenge in working with complex experience-centered domains is that it is hard for nonexperts to understand the domain in order to model it. In this paper we present DAISY, the Design Aid for Intelligent Support SYstems. It is a software design methodology for constructing decision support systems in complex, experience-based domains. DAISY address the specialized challenges of these domains by augmenting existing cognitive engineering methodologies. In particular, DAISY provides a method for identifying the specialized needs of users within a specific range of domain experience. Thus, it can help software designers to understand, "What does the domain expert need?" or "What does a trained novice need?" To help system designers manage the complexity of modeling unfamiliar experience-centered domains, it provides a tool called a Time/Activity matrix. To illustrate each of DAISY's steps, we will used the development of a decision support system, Fox. Fox assists expert military planners by rapidly generating alternative plans. This is a cognitively difficult, time critical task with life and death consequences.