HDF5format

HDF5 format refers to the HDF5 data model and binary file format used to store and organize large, complex datasets. Developed and maintained by The HDF Group, it is widely adopted in scientific computing due to its flexibility, scalability, and ability to preserve rich metadata across platforms and programming languages.

HDF5 files organize data hierarchically using objects called groups and datasets. Groups provide a filesystem-like namespace, while datasets store multi-dimensional arrays of primitive or compound data types. Attributes can be attached to both groups and datasets to record metadata.

The data model supports a rich set of data types, dataspace definitions, and dataset creation properties that control layout and I/O. Important features include chunked storage for efficient partial I/O, compression and filters, and support for extendible datasets with unlimited dimensions.

On disk, the format uses a binary layout with a metadata layer that enables rapid indexing, caching, and random access. It supports virtual file drivers and external storage options, allowing use with different file systems and parallel I/O environments. The format is designed for cross-platform portability.

Programming language support is broad, with a reference C API and bindings for C++, Fortran, Java, and Python (notably via h5py). Other languages such as MATLAB and R also provide interfaces. The HDFView utility offers graphical inspection and basic analytics of HDF5 files.

HDF5 underpins many scientific workflows and data standards; it is used in fields from climate modeling to high-energy physics and biology. NetCDF-4 uses the HDF5 format as its storage backend, enabling interoperability with NetCDF tools while benefiting from HDF5 features.

The specification and library are maintained by The HDF Group, with ongoing development to add features, improve performance, and ensure backward compatibility across versions.