PyModESt: A Python Framework for Staging of Geo-referenced Data on the Collaborative Climate Community Grid (C3-Grid)

Abstract

A serious problem in scientific data management is the integration of different distributed project infrastructures to reach unified provision of geo-referenced data. The C3-Grid data interface enables users to find the earth-system data they are looking for over ISO-metadata sets, decoupling most data conversion and projection steps from the data interfaces into independent workflow modules. Thus data providers can uniformly deliver user-selected parts of their data sets “as-is”, relying on the tools they already have and are experienced in using. This presentation is about a DLR-developed Python framework that further eases the implementation of the data-set- and resource-specific staging scripts, letting the developers focus on the essentials, exploit the extensibility and maintainability through freely available Python features and lowering knowledge barriers to make own data sets accessible in a common infrastructure based on C3-Grid achievements.