Data de- and redimensioning for optimized brokering access

Data brokering systems aim to facilitate the exchange of data and models between disciplines in an increasingly transparent manner thereby accelerating scientific discovery. Researchers from many different, yet complimentary geoscience disciplines need to access cross field datasets from different fields with significantly different data formats, and in most cases differing time and space dimensionality than their own field commonly uses. This causes problems with large datasets with different time and space dimensions, as the difference in dimension often means that the entire dataset has to be read in order to provide the limited information the researcher is interested in. In this poster we present methods for removing the dimensionality from datasets, both physically on the data serving side as well demonstrate de- and redimensioning datasets from a broker based virtual perspective so the data brokering system can quickly access the smaller subset of data in the correct dimensionality for any given field.