As data set size and complexity grows, the problem of managing and analyzing scientific data sets grows. The ASC SDM project develops tools that assist scientists in understanding and organizing their data and information. The project has a tool development effort centered on metadata techniques for managing and simplifying data access, and a research effort. The research project, known as Sapphire, focuses on applying feature extraction, data mining, and pattern recognition techniques to large scale data.
The SDM project aims to deliver services for creating, storing, retrieving, and searching data through an integrated environment that supports end users' work as much within the context of that work as possible. For example, a calculation summary tool ties together simulation inputs and results and reduces the use of arcane commands, lengthy and obscure path names, and time focused on transferring data. A mining tool creates metadata behind the scenes that later can be used in searches or presentation of the metadata. Graphical directory browsers can launch end users' applications and can be configured to recall lengthy command sequences.
Metadata Tools
For more information about ASC Scientific Data Management, contact either Jeff Long or Becky Springmeyer.