CALL FOR PAPERS: FIRST WORKSHOP ON KNOWLEDGE DISCOVERY FROM CLIMATE DATA
		     PREDICTION, EXTREMES, AND IMPACTS (Climate-KDD)

IEEE International Conference in Data Mining, Miami, FL, December 6-9, 2009

Website: http://www.nd.edu/~dial/climkd09

The Climate Change Challenge: Climate change and consequences are increasingly
being recognized as among the most significant challenges facing humanity and
our planet. The Fourth Assessment Report of the Intergovernmental Panel on
Climate Change (IPCC AR4) shared the 2007 Nobel Peace Prize for providing
evidence of human-induced warming at global and century scales. The clear and
present need is to develop regional assessments of climate change and
consequences, including but not limited to large regional hydro-meteorological
changes and extreme events, extreme stresses on ecology, environment, key
resources, critical infrastructures and society, as well as detection or
attribution and a comprehensive characterization or reduction of uncertainty.
A clear link needs to be developed between the science of climate change and
the science of impacts analysis for facilitating the process.

Innovations in Data Mining: The analysis of climate data, both observed and
model-generated, poses a number of unique challenges: (i) massive quantities
of data are available for mining, (ii) the data is spatially and temporally
correlated so the IID assumption does not apply, (iii) the data-generating
processes are known to be non-linear, (iv) the data is potentially noisy,
and (v) extreme events exist within the data. Climate data mining is based
on geographic data and inherits the attributes of space-time data mining.
In addition, climate relationships are nonlinear, spatial correlations can be
over long range (teleconnections) and have long memory in time. Thus, in
addition to new or state of the art tools from temporal, spatial and
spatiotemporal data mining, new methods from nonlinear modeling and analysis
are motivated along with analysis of massive data for teleconnections and
long-memory dependence.

Climate extremes may be inclusively defined as severe weather events as well
as significant regional changes in hydro-meteorology, which are caused or
exacerbated by climate change, and climate modelers and statisticians struggle
to develop precise projections of such phenomena. The ability to develop
predictive insights about extremes motivates the need to develop indices based
on nonlinear dimensionality reduction and anomaly analysis in spacetime
processes from massive data. Knowledge discovery is broadly construed here to
include high-performance data mining of geographically-distributed climate
model outputs and observations, analysis of space-time correlations and
teleconnections, geographical analyses of extremes and their consequences
obtained through fusion of heterogeneous climate and GIS data along with their
derivatives, geospatial-temporal uncertainty quantification, as well as
scalable geo-visualization for decision support.

Topics of Interest:
- Theoretical foundations of mining massive climate datasets for patterns,
  trends, or extremes
- Algorithms and implementations for the analysis of climate data, including:
	> Patterns / Clusters
	> Extremes / Outliers
	> Change Detection
	> Correlation and Teleconnections
	> Predictive Models
- Space-time prediction of climate variables and/or climate extremes
- Methods addressing the role of uncertainty in space-time prediction
- High-performance computing solutions for the analysis of climate data
- Studies assessing the impacts of climate change and/or extremes
- Applications that demonstrate success stories of knowledge discovery
  from climate data

PAPER SUBMISSIONS
We invite regular paper submissions, work-in-progress, demo papers, and
position papers. The papers must follow the IEEE ICDM format. The regular
papers can be up to 10 pages in length in the IEEE ICDM format. The position
and work-in-progress papers should be a minimum of 2 pages in the IEEE ICDM
format. We very much welcome demo papers that cater to GIS and visualization
aspects of climate data sciences. We especially encourage inter-disciplinary
papers. All papers will be reviewed by the Program Committee on the basis of
technical quality, relevance to workshop topics, originality, significance,
and clarity. Please use the submission form on the ICDM'09 website to submit
your paper. More details will be made available on our website.

IMPORTANT DATES
Paper Submission:		August 8, 2009
Notification to Authors:	September 8, 2009
Camera-Ready Papers:		September 28, 2009