Ophidia is a CMCC Foundation research effort addressing Big Data challenges for eScience. The Ophidia framework represents an open source solution for the analysis of scientific multi-dimensional data, joining HPC paradigms and Big Data approaches. It provides an environment targeting High Performance Data Analytics (HPDA) through parallel and in-memory data processing, data-driven task scheduling and server-side analysis. The framework exploits an array-based storage model, leveraging the datacube abstraction from OLAP systems, and a hierarchical storage organisation to partition and distribute large multi-dimensional scientific datasets over multiple nodes. Ophidia is primarily used in the climate change domain, although it has also been successfully exploited in other scientific domains.

Software license: GPLv3.


The framework is composed by different software components. The source code for the various components is available on GitHub.

The installation guide is available in the documentation.

Ophidia can also be installed through the Spack package manager.

For the client side, Ophidia also provides the Python bindings, called PyOphidia. To install PyOphidia:

pip install pyophidia

or to install in a Conda environment:

conda install -c conda-forge pyophidia

The PyOphidia documentation (Installation, usage, examples and tutorial) can be found here.


Ophidia provides features for data management and analysis, such as:

  • data reduction and subsetting

  • data intercomparison

  • array processing

  • time series analysis

  • statistical and mathematical operations

  • data manipulation and transformation

  • interactive data exploration

The user guide documents all the available Ophidia features.