Topics of particular interest include, but are not limited to, the following, as they relate to scientific and statistical data management:

• Stream data management, e.g., storage, organization, compression, indexing and querying

• Stream data analysis, e.g., summarization, statistical analysis, pattern matching, pattern discovery, learning, and prediction

• Modeling and representation of streaming data

• Case studies, particularly those at scale-of-consequence for health, energy, and environment

• Integration and exchange of data, including the federation and management of institutional data repositories

• Design, implementation, optimization of scientific workflows

• System architectures for scientific and statistical data management and analysis

• Querying of scientific data, including spatial, temporal, and streaming data

• Mining and analysis of large-scale datasets, especially on new and emerging hardware and environments

• Visualization and exploration

• Information retrieval and text mining

• Knowledge discovery, clustering, data mining