Abstract

In order to drive discovery from data, scientists rely on accurate, up-to-date descriptions of data. Management of scientific data is often split between storage systems for large, bulk collections of data and specialized databases for detailed descriptive information about data, known as metadata, organized in a database schema. Without such schema and descriptive metadata, scientific data would be lost. Yet scientific data is among the most challenging to manage due to schema evolution brought on by changing experiments, new technology and instruments, changing methods, emerging standards, and different conceptualizations between investigators.

Date

2022

Authors

Robert Edward Schuler

Institution

University of Southern California