Reports and Papers

Fedra, K. (1995)
Decision support for natural resources management:
Models, GIS and expert systems.
AI Applications, 9/3 (1995) pp 3-19.

The User Interface

The examples of integration discussed above mainly refer to internal integration, ie., linking components of an information system. There are, however, two more important dimensions to integration that need to be considered: integration with the user and integration with the information sources of a system (compare Figure 1 ). Important issues here are interaction and visualization, intelligence, and customization, that is the integration into the institutional framework of a system's intended use.

Interaction is a central feature of any effective man--machine system: a real-time dialogue, including explanation, allows the user to define and explore a problem incrementally in response to immediate answers from the system; fast and powerful systems with modern processor technology can offer the possibility to simulate dynamic processes with animated output, and they can provide a high degree of responsiveness that is essential to maintain a successful dialogue and direct control over the software.

Visualization provides the band-width necessary to communicate and understand large amounts of highly structured information, and permits the development of an intuitive understanding of processes and interdependencies, of spatial and temporal patterns, and complex systems in general. Also, many of the problem components in a real-world planning or management situation, such as risk or reliability, are rather abstract: a graphical representation of such concepts makes them tangible objects that can literally be manipulated and understood intuitively.

Intelligence requires software to be knowledgeable not only about its own possibilities and constraints, but also about the application domain and about the user, ie., the context of its use. Defaults and predefined options in a menu system, sensitivity to context and history of use, built-in estimation methods, learning, or alternative ways of problem specification depending on the user can all be achieved by the integration of expert systems technology in the user interface and in the system itself.

Customization is based on the direct involvement of the end-user, and the consideration of institutional context and the specifics of the problem domain in systems design and development. It is the users view of the problem and their experience in many aspects of the management and decision making process that the system is designed to support. This then must be central to a system's implementation to provide the basis for user acceptance and efficient use.

Decision support systems, and their interfaces, are representations of the problems they address as much as of the planning and decision making processes they are designed to support. In the latter field, if not also in the former, their users are the real experts. Thus, their expertise and experience needs to be included in the systems. As a consequence, users must be involved in the design and development, so that they can accept responsibility and ownership for the software system.

Institutional integration also must look at aspects such as user training, data entry, maintenance issues of keeping systems current and operational, providing adaptations and updates, etc. Any complex information system has more than one user at more than one level of technical competence and with different roles within an institution. Different users have different requirements that need to be supported: flexibility and adaptability are therefore important features. Systems must be able to grow with their users. Therefore, the institutional commitment and technical infrastructure to keep a system alive and evolving are as important as the scientific and technical quality of the original software system.

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