Awowale et al. - Simplifying analysis of hierarchical HDF5 and NetCDF4 files with xarray-datatree

DataTree provides a simplified way to work with hierarchical HDF5 and NetCDF4 files by representing groups as a tree structure, avoiding the need to open multiple datasets separately

NASA has over 100 petabytes of Earth observation data stored in HDF format, with expected growth to 600 petabytes from new missions. Managing and accessing this data efficiently is a key challenge

Current tools like X-Ray and NetCDF4 require specifying groups individually to open data, which is inefficient and leads to complex code. DataTree allows viewing the entire dataset hierarchy at once

DataTree integrates with X-Ray to provide lazy loading, efficient computations, and familiar X-Ray operations while maintaining the hierarchical structure of the data

The tool enables cloud-optimized access to HDF data by reducing unnecessary file operations and memory usage compared to traditional methods

DataTree simplifies subsetting operations by eliminating the need to flatten/unflatten data structures and copy datasets multiple times

The project represents a collaboration between NASA and the open source community, with NASA engineers contributing to improve accessibility of Earth science data

DataTree will be integrated into the main X-Ray package in an upcoming release, providing long-term support and standardization

The tool supports various data formats beyond just HDF5/NetCDF4 and can be extended to work with other hierarchical data formats

Current implementations show significant performance improvements, with operations being up to 1000x faster compared to naive implementations when working with nested groups