Schema-Independent and Schema-Friendly Scientific Metadata Management
Source: Indiana University
Computational science is creating a deluge of data, and being able to reuse this data requires detailed descriptive metadata. Scientific communities have developed detailed metadata schemas to describe data products, but this metadata must be captured as workflows execute. The authors' research has identified characteristics of scientific schemas that can be exploited to efficiently capture and search this metadata based on the schemas specific to each community, but using an easily adaptable framework. Computational science grids generate huge volumes of scientific data through the workflow orchestrated activities of their domain science users.