“Intelligent Systems for Geosciences: An Essential Research Agenda”
Communications of the ACM, January 2019, Vol. 62 No. 1, Pages 76-84
Review Articles
By Yolanda Gil, Suzanne A. Pierce, Hassan Babaie, Arindam Banerjee, Kirk Borne, et. al.
“This body of research will lead to a new generation of knowledge-rich intelligent systems that contain rich-knowledge and context in addition to data, enabling fundamentally new forms of reasoning, autonomy, learning, and interaction.
Novel research is needed to develop new machine learning approaches that incorporate knowledge about geoscience processes and use it effectively to supplement the small sample size of the data.”
Many aspects of geosciences pose novel problems for intelligent systems research. Geoscience data is challenging because it tends to be uncertain, intermittent, sparse, multiresolution, and multi-scale. Geosciences processes and objects often have amorphous spatiotemporal boundaries. The lack of ground truth makes model evaluation, testing, and comparison difficult. Overcoming these challenges requires breakthroughs that would significantly transform intelligent systems, while greatly benefiting the geosciences in turn. Although there have been significant and beneficial interactions between the intelligent systems and geosciences communities, the potential for synergistic research in intelligent systems for geosciences is largely untapped. A recently launched Research Coordination Network on Intelligent Systems for Geosciences followed a workshop at the National Science Foundation on this topic. This expanding network builds on the momentum of the NSF EarthCube initiative for geosciences, and is driven by practical problems in Earth, ocean, atmospheric, polar, and geospace sciences. Based on discussions and activities within this network, this article presents a research agenda for intelligent systems inspired by geosciences challenges.
