Trading Consistency for Scalability in Scientific Metadata

Long-term repositories that are able to represent the detailed descriptive metadata of scientific data have been recognized as key to both data reuse and preservation of the initial investment in generating the data. Detailed metadata captured during scientific investigation not only enables the efficient discovery of relevant data sets but also is a source for exploring ongoing activity. In XMC Cat metadata catalog, an XML catalog that uses a novel hybrid model to store XML to a relational database, we exploit differences in the temporal utility between browse and search metadata to selectively relax the consistency model used. By ensuring only eventual consistency on parts of the solution, we determine through experimental analysis that the performance and scalability of the catalog can be substantially improved.