The recent explosive growth in computer power and connectivity is reshaping relationships among people and organizations, and transforming the processes of discovery, learning, and communication. As a result of the technological advances we have unprecedented opportunities for providing rapid and efficient access to enormous amounts of knowledge and information; for studying vastly more complex systems than was hitherto possible; and for advancing in fundamental ways our understanding of learning and intelligence in living and engineered systems. NSF's Knowledge and Distributed Intelligence (KDI) theme is a Foundation-wide effort to promote the realization of these opportunities.

NSF aims to achieve, across the scientific and engineering communities, the next generation of human capability to generate, model, and represent more complex and cross-disciplinary scientific data from new sources and at enormously varying scales; to transform this information into knowledge by combining and analyzing it in new ways; to deepen our understanding of learning and intelligence in natural and artificial systems; to explore the cognitive, ethical, educational, legal, and social implications of new types of learning, knowledge, and interactivity; and to collaborate in sharing knowledge and working together interactively.

To achieve the aims of KDI, proposals are solicited from individuals or groups for research that is inherently multi disciplinary or that, while lying within a single discipline, has clear impact on at least one other discipline. In FY 1998, KDI will have three foci: Knowledge Networking (KN); Learning and Intelligent Systems (LIS); and New Computational Challenges (NCC).

Knowledge Networking (KN) focuses on the integration of knowledge from different sources and domains across space and time. The goal of KN research is to achieve new levels of knowledge integration,information flow, and interactivity among people, organizations, and communities, and to deepen our understanding of the ethical, legal, and social implications of knowledge networking.

Learning and Intelligent Systems (LIS), an ongoing program, seeks to stimulate multi disciplinary research that will unify experimentally and theoretically derived concepts related to learning and intelligent systems, and that will promote the use and development of information technologies in learning and discovery across a wide variety of fields. LIS emphasizes research that advances basic understanding of learning and intelligence in natural and artificial systems, as well as research that supports the development of tools and environments to test and apply this understanding in real situations.

New Computational Challenges (NCC) focuses on research and tools needed to discover, model, simulate, analyze, display, or understand complex phenomena, to control resources and deal with massive volumes of data in real time, and to predict the behavior of complex systems. These aims will require major advances in hardware and software to handle complexity, representation, and scale, to enable distributed collaboration, and to facilitate real-time interactions and control.