Abstract

Today data are being collected by a vast number of instruments in every discipline of science. In addition to raw data, new products are created every day as a result of processing existing data and running simulations in order to understand observed data. As the sizes of the datasets grow into the petascale range, and as data are being shared among and across scientific communities, the importance of diligently recoding the meaning of data and the way they were produced increases dramatically. One can think of metadata as data descriptions that assign meaning to the data, and data provenance as the information about how data was derived. Both are critical to the ability to interpret a particular data item. Even when the same individual is collecting the data and interpreting them, metadata and provenance are important. However, today, the key drivers for the capture and management of data descriptions are …

Date

2009

Authors

Ewa Deelman, Bruce Berriman, Ann Chervenak, Oscar Corcho, Paul Groth, Luc Moreau

Book

Scientific Data Management

Pages

465-498

Publisher

Chapman and Hall/CRC