The 2008 International Workshop on Spatial and Spatiotemporal Data Mining (SSTDM-08) builds on the success of previous workshops (SSTDM/ICDM-06, SSTDM/ICDM-07, STDM/ICDE-07). In addition, this year we have combined SSTDM with the workshop on "Data Mining for GeoInformatics," thus bringing under a single platform both vector and raster datatypes, and a broader set of topics, including theoretical as well as applied issues.

Synopsis: With advances in remote sensors, sensor networks, and the proliferation of location sensing devices in daily life activities and common business practices, the generation of disparate, dynamic, and geographically distributed spatiotemporal data has exploded in recent years. In addition, significant progress in ground, air- and space-borne sensor technologies has led to an unprecedented access to earth science data for scientists from different disciplines, interested in studying the complementary nature of different parameters. These developments are quickly leading towards a data-rich but information-poor environment. The rate at which geospatial data are being generated clearly exceeds our ability to organize and analyze them to extract patterns critical for understanding in a timely manner a dynamically changing world. Computer science and geoinformatics are collaborating in order to address these scientific and computational challenges and provide innovative and effective solutions.

More specifically, efficient and reliable data mining techniques are needed for extracting useful geoinformation from large heterogeneous, often multi-modal spatiotemporal datasets. Traditional data mining techniques are ineffective as they do not incorporate the idiosyncrasies of the spatial domain, which include (but are not limited to) spatial autocorrelation, spatial context, and spatial constraints. Extracting useful geoinformation from several terabytes of streaming multi-modal data per day also demands the use of modern computing in all its forms. Thus, we invite computer science and geoinformatics researchers to participate in this event in order to share, contribute, and discuss the emerging challenges in spatial and spatiotemporal data mining.

Topics: The major topics of interest to the workshop include but are not limited to:

Proceedings: Accepted papers will be included in a ICDM Workshop Proceedings volume, to be published by IEEE Computer Society Press, which will also be included in the IEEE Digital Library. In addition, selected papers are going to be included in a planned journal special issue.