6.5
Iris: a data analysis & visualisation framework

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner
Tuesday, 8 January 2013: 4:30 PM
Iris: a data analysis & visualisation framework
Room 12B (Austin Convention Center)
Richard Hattersley, Met Office, Exeter, United Kingdom

The need to establish closer collaboration with different organisations and partners has highlighted the need for a range of tools and libraries that can be shared and developed as a community. To address this, the Met Office started a development programme to investigate and distil the requirements of our scientific community, and identify an appropriate technology “ecosystem”.

The result of the development programme was to select Python along with NumPy, SciPy, and Matplotlib to be the foundation packages on which to build a new data analysis and visualisation framework. The core of that framework is a new package called Iris. The Iris package implements a data model to create a data abstraction layer which isolates analysis and visualisation code from data format specifics. The data model we have chosen is the CF Data Model. The implementation of this model we have called an Iris Cube.

Iris currently supports read/write access to a range of data formats, including (CF-)netCDF, GRIB, and PP; fundamental data manipulation operations, such as arithmetic, interpolation, and statistics; and a range of integrated plotting options. The Met Office has published Iris under a LGPL license so that it can be used and developed by the scientific community.