CLIMATE-KDD 2010 - SECOND WORKSHOP ON KNOWLEDGE DISCOVERY FROM CLIMATE DATA PREDICTION, EXTREMES, AND IMPACTS (Climate-KDD)

Website datamining.it.uts.edu.au/icdm10/index.php/workshops | Edit Freely

Category CLIMATE-KDD 2010

Deadline: July 23, 2010 | Date: December 13, 2010

Venue/Country: Sydney, Australia

Updated: 2010-06-04 19:32:22 (GMT+9)

Call For Papers - CFP

PREDICTION, EXTREMES, AND IMPACTS (Climate-KDD)

IEEE International Conference in Data Mining, Sydney, Autralia, December 13-17, 2010

Website: http://www.nd.edu/~dial/climkd10

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: July 23, 2010

Notification to Authors: September 20, 2010

Camera-Ready Papers: October 11, 2010

Workshop: December 13, 2010