Mining Big Data in Climate and Environment

In conjunction with 17th SIAM International Conference on Data Mining (SDM 2017)  April 27 - 29, 2017, Houston, Texas, USA
Workshop Date: Saturday, April 29, 2017

Climate and environmental sciences have recently experienced a rapid transformation from a data-poor to a data-rich environment. In particular, climate related observations from remote sensors on satellites and weather radars, or from in situ sensors and sensor networks, as well as outputs of climate or Earth system models from large-scale computational platforms, provided terabytes of temporal, spatial and spatio-temporal data. In addition, the rapid growth of geographical information systems have led to the availability of multi-source data. These massive and information rich datasets offer a huge potential for advancing the science of climate change and impacts on the system of interconnected and interdependent food, energy and water systems. This workshop will bring together researchers who are interested in addressing related environmental concerns by advancing the state of the art in spatio-temporal analytics. A special focus will be on the understanding the nexus of food, energy, water, and ecosystems and their interaction with changing climate.

The workshop will include invited talks by leading experts, panel discussions, oral presentations and a poster session for contributed papers.

This workshop should be of interest to researchers in data mining, machine learning, statistics who are working on or interested in working on environmental problems as well as researchers from a broad range of environmental sciences interested in engaging the data mining community.