It’s a good feeling when you are part of a world changing in a positive direction. I just came back from the Climate Informatics workshop in Boulder , CO (always an amazing place to visit, especially in the Fall), where I witnessed our field evolving towards smarter approaches to large-scale data analysis. Informatics being a relatively new term, so we spent some time pondering what it means. One definition I like is “the study of the processing, management, and retrieval of information as applied to climate science”. Broadly speaking, the workshop brought together a 50/50 mix of climate scientists on one side, and “information folks” on the other side, be they statisticians, computer scientists, and the machine learning community that swims in between.
It’s always exciting to see smart people take an interest in your field, and there were definitely some ah-ah moments for me in what machine learning could bring into the study of climate variability. The talks are available here in mp4 format.
Before we can bring the power of automation to the study of past climates, however, we must structure them in a way that enables data mining. This is currently not the case, and something that the community is working towards. Towards a semantic web for paleoclimatology is a recently submitted paper that explains the problem and proposes some solutions ; i hope some of you find it useful, especially the paleoclimatology community!
Back to work ; hoping to post more than once a year in the future…