DMESS 2012 - Third Worskhop on Data Mining in Earth System Science (DMESS 2012)

Spanning many orders of magnitude in time and space scales, Earth science data are increasingly large and complex, and often represent very long time series, making such data difficult to analyze, visualize, interpret, and understand. Moreover, advanced electronic data storage technologies have enabled the creation of large repositories of observational data, while modern high performance computing capacity has enabled the creation of detailed empirical and process-based models that produce copious output across all these time and space scales. The resulting “explosion” of heterogeneous, multi-disciplinary Earth science data has rendered traditional means of integration and analysis ineffective, necessitating the application of new analysis methods and the development of highly scalable software tools for synthesis, comparison, and visualization. This workshop explores various data mining approaches to understand Earth science data, emphasizing the technological challenges associated with utilizing very large and long time series geospatial data sets. Especially encouraged are original research papers describing applications of data mining methods?including cluster analysis, empirical orthogonal functions (EOFs), genetic algorithms, neural networks, and other machine-learning techniques?that support analysis and discovery in climate, water resources, geology, ecology, and environmental sciences research.