Addressing the ambitious research agendas put forward by many scientific disciplines requires meeting a multitude of challenges in intelligent systems, information sciences, and human-computer interaction. There are many aspects of the scientific discovery process that our community could help automate, facilitate, or make more efficient through artificial intelligence techniques. For example, although considerable efforts have been directed toward data modeling and integration, these activities continue to demand large investments of scientists’ time and effort. The scientific literature continues to grow and is becoming more and more unmanageable for researchers operating in the most active disciplines. Better interfaces for collaboration, visualization, and understanding would significantly improve scientific practice. Scientific data, publications, and tools could be published in open formats with appropriate semantic descriptions and metadata annotations to improve sharing and dissemination. Opportunities for broader participation in well-defined scientific tasks enable human contributors to provide large amounts of data, annotations, or complex processing results that could not otherwise be obtained. These are just some examples of areas where there are opportunities for artificial intelligent techniques could make a difference. Improvements and innovations across the spectrum of scientific processes and activities will have a profound impact on the rate of scientific discoveries. This symposium provided a forum for researchers interested in understanding the role of AI techniques in improving or innovating scientific processes.
