The workshop aims to identify the research challenges and opportunities for transforming the scientific discovery process through advances in computing and information sciences in general, and intelligent systems in particular. It seeks to define a research agenda in Discovery Informatics. The workshop is organized around three themes: (1) efficient experimentation and discovery processes, (2) practical issues in building and refining predictive models from scientific data, and (3) social computing for science.
The participants include experts and visionaries in the areas of knowledge representation and inference, machine learning and data mining, experiment design and planning, information integration, computational models of discovery, collaborative technologies, robotics, social networks, visualization, and representative application (science) domains.
Research in Discovery Informatics is expected to integrate advances in multiple subdisciplines of artificial intelligence and cognitive science to develop the next generation informatics driven exploratory apparatus for scientific discovery. The resulting formal frameworks and computational tools have the potential to not only accelerate discovery but enable new modes of discovery by providing the tools that empower scientists to reach across disciplinary boundaries. Such tools can also contribute to enhanced modes of teaching and learning in science, technology, engineering, and mathematics (STEM) disciplines.
The results of the workshop (including the workshop report) will be freely disseminated to the larger scientific research and educational community.
Computer science research has been motivated by scientific problems, including distributed sensor networks, high-end computing, distributed systems, scalable databases, statistical and data mining algorithms, computer networks and the web itself. We are now facing the limits of our ability to gain insight from the volume, variety, and velocity of available data, posing fundamental challenges that can only be addressed through symbiotic advances in computing. Our ability to understand and gain insight from data of unprecedented complexity could be greatly increased with appropriate intelligent assistance and automation. The Workshop on Discovery Informatics was convened to articulate the research challenges concerned with the management of knowledge and of the complex processes involved in scientific discovery. Workshop participants identified an expansive range of fundamental research challenges for information and intelligent systems to support scientific discovery. Discovery Informatics focuses on computing advances aimed at identifying scientific discovery processes that require knowledge assimilation and reasoning, and applying principles of intelligent computing and information systems in order to understand, automate, improve, and innovate any aspects of those processes. A new initiative in Discovery Informatics would enable and catalyze the transformational innovations needed to have a broad impact on the improvement and innovation of scientific discovery processes. Discovery Informatics would require advancing basic research in many areas of computing, including: information extraction and text understanding to process publications and lab notebooks; synthesis of models from first principles, hypotheses, or data analysis; dynamic and adaptive design of data analysis methods; design, execution, and steering of experiments; selective data collection; data and model visualization; theory and model revision; collaborative activities that improve data understanding and synthesis; intelligent interfaces for scientists; design of new processes for scientific discovery; and computational mechanisms to represent and communicate scientific knowledge to colleagues, researchers in other disciplines, students, and the public. Discovery Informatics will accelerate 21st century science and will have outcomes vital to the nation in numerous ways. National security is in severe need of better technologies for data analysis, noticing the unusual, and discovering patterns. Personal health and preventive medicine depend on our ability to enable people to contribute to the scientific enterprise in meaningful ways, by contributing data, analysis, personal histories, and sensor data. Our future relies on a better understanding of environmental and sustainability factors that is well beyond our current abilities. Our national competitiveness will be significantly boosted by a significant push in our nation’s capabilities as a knowledge economy that would result from a renewed strength in Discovery Informatics. Discovery Informatics will advance the frontiers of computing, particularly in emerging areas of information and intelligent systems, while enabling new discoveries and innovations in all areas of science and engineering.
