Co-convened by: Forrest M. Hoffman, J. Walter Larson, and Richard Tran Mills
Computational Science, University of Tsukuba, Japan
Due to the continuing uncertainty about the situation in Japan,
the conference will now be held on the beautiful campus of
Singapore's Nanyang Technological University.
June 1–3, 2011
From field-scale measurements to global climate simulations and remote sensing, very large and long time series databases of Earth Science data are difficult to analyze and interpret. Data mining techniques—like cluster analysis, empirical orthogonal functions (EOFs), phase-space reconstruction, and neural networks—are being applied to problems of segmentation, feature extraction, model-data comparison, and validation. The size and complexity of Earth Science data, however, exceed the limits of most analysis tools. Scalable tools running on parallel supercomputers are required to analyze data of this size. This workshop will demonstrate how data mining techniques are applied in the Earth Sciences and describe innovative computer science methods that support analysis and discovery in Earth Sciences.
Authors are invited to submit manuscripts of up to 10 (A4) pages reporting original, unpublished research and recent developments/theoretical considerations in applications of data mining to Earth sciences by
January 8, 2011 January 26, 2011. Accepted papers will printed in the conference proceedings published by Elsevier Science in the open-access Procedia Computer Science series. Submitted papers must be camera-ready and formatted according to the rules of Procedia Computer Science. Submission implies the willingness of at least one of the authors to register and present the paper.
Please submit your paper via the conference website at http://www.iccs-meeting.org/iccs2011/papers/upload.php and select the workshop “Data Mining in Earth System Science (DMESS 2011)”.
|Full paper submission:|
|Notification of paper acceptance:||February 20, 2011|
|Final camera-ready papers due:||March 7, 2011|
|Early registration opens:||Feburary 15, 2011|
|Early registration closes:||March 31, 2011|
|E-mail:||dmess2011 at climatemodeling dot org|
This workshop will contribute to the field of Computational Science by creating a forum for original research papers and presentations from leading computational and earth scientists who are applying data mining techniques on advanced computing platforms (HPC systems, clusters, grids and clouds) to distill knowledge from the massive—and growing—data sets created by the earth science community.
Forrest M. Hoffman has been developing software for data mining using high performance computing (HPC) and apply data mining methods to problems in landscape ecology, remote sensing, and climate analyses for more than a decade. Forrest co-convened the GeoComputation workshop at ICCS 2009 and recently presented an invited talk on geospatiotemporal data mining at the 2010 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). Forrest's publication list is available at http://www.climatemodeling.org/~forrest/pubs.
J. Walter Larson is a leader in the development of coupling software for simulation of complex systems, most notably as the co-lead developer of the Model Coupling Toolkit (http://mcs.anl.gov/mct) and as one of the developers of the coupling infrastructure in the Community Climate System Model. He has published papers in the fields of mathematical and plasma physics, climate, data assimilation, and computational science (http://people.physics.anu.edu.au/~jwl105/Pubs).
Richard Tran Mills has conducted research in high performance computing, software for iterative solution of sparse algebraic systems, computational hydrology, geospatiotemporal data mining, computational hydrology, and execution context-aware software. He has contributed to the PETSc PDE-solver framework and is a principal author of the subsurface flow and reactive transport code PFLOTRAN, which is being used on the largest-scale supercomputers in the world to study topics such as radionuclide transport and geologic carbon sequestration.