Skip to Main Content
Scientific datasets, such as HDF5 and PnetCDF, have been used widely in many scientific applications. These data formats and libraries provide essential support for data analysis in scientific discovery and innovations. In this research, we present an approach to boost data analysis, namely Fast Analysis with Statistical Metadata (FASM), via data sub setting and integrating a small amount of statistics into datasets. We discuss how the FASM can improve data analysis performance. It is currently evaluated with the PnetCDF on synthetic and real data, but can also be implemented in other libraries. The FASM can potentially lead to a new dataset design and can have an impact on data analysis.