Getting Started

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Getting Started#

Obtain a concise overview of the h5rdmtoolbox and its functionalities.

The “HDF5 Research Data Management Toolbox” (h5rdmtoolbox) is a python package supporting everyone who is working with HDF5 to achieve a sustainable data lifecycle which follows the FAIR (Findable, Accessible, Interoperable, Reusable) principles. It specifically supports the five main steps of

  1. Planning (defining a domain- or problem-specific metadata convention and an layout defining the internal structure of HDF5 files)

  2. Collecting data (creating HDF5 files from scratch or converting to HDF5 files from other sources)

  3. Analyzing and processing data (Plotting, processing data while keeping the HDF5 attributes by using xarray)

  4. Sharing data (either into a repository like e.g. Zenodo or into a database)

  5. Reusing data (Searching data in databases, local file structures or online repositories like Zenodo).

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Overview#

The h5rdmtoolbox is organized in five sub-packages corresponding to main features, which are needed to achieve a sustainable data lifecycle. The sub-packages are:

Besides the wrapper, which uses the convention sub-package, all sub-packages are independent of each other and can be developed and used separately.

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Contents