Knowledge Networking (KN) The aim of Knowledge Networking (KN) is to facilitate the evolution from distributed information access to new technical and human capabilities for interactive knowledge creation and use. Through this evolution interdisciplinary communities can be joined in sharing data and building knowledge to address complex problems traditionally treated within disciplinary boundaries. KN focuses on the seamless integration of knowledge and activity across content domains, space, time, and people. Modern computing and communications systems are beginning to provide the infrastructure to send information anywhere, anytime, in mass quantities: they provide very high connectivity. Further advances in computing and communications hold the promise of fundamentally accelerating the creation and distribution of information. The creation of new knowledge in groups, organizations, and scientific communities requires additional advances beyond the ability to collect, process, and transmit large amounts of data. Building upon the growing capability for connectivity, the Knowledge Networking initiative is designed to support the creation and thorough understanding of: New forms of and tools for data gathering, such as sharable remote instruments and large-scale web-based experimentation; New ways of transforming distributed information into seamlessly sharable, universally accessible knowledge; Appropriate processing and integration of knowledge from different sources, domains, and non-text media; Useful communication and interaction across disciplines, languages, cultures; New tools and means of working together over distance and time; Efficacious socio-technical arrangements for teams, organizations, classrooms, or communities, working together over distance and time; Cognitive dimensions of knowledge integration and interactivity; Deepening understanding of the ethical, legal, and social implications of new developments in knowledge networking; and, Sustainable integration, long term use, and life-cycle effectiveness of knowledge networks. Both technological capability and human interaction in the overall scientific process must evolve if knowledge networking is to reach its full potential. Achieving the new capabilities envisioned for Knowledge Networking and making them widespread, universally accessible, and sustainable over the long term specifically requires research into the human processes involved in creating and disseminating knowledge. Multidisciplinary knowledge networking efforts will fail unless we understand and provide for the environments that enable skill sets, conceptual models, and values to be rapidly shared across disparate fields, and that account for the institutional and cultural dimensions of knowledge sharing and interaction.