Scientific file formats in code

File formats are decade-scale decisions: data outlives the code that wrote it, and a format choice made in a script today determines whether a dataset is readable, FAIR and efficient in ten years. The guiding principle is SELF-DESCRIBING data: a file a stranger can open and understand - variables named, units attached, provenance noted - without emailing the author (rseng-data-management owns the surrounding practice; this skill owns the format engineering).

Choosing a format

• Multidimensional arrays (grids, time series stacks, images, simulation output): NetCDF (atmosphere/ocean/climate lingua franca, built on HDF5) or HDF5 directly; both hierarchical, self-describing, partial-read capable and language-portable.
• Tabular data at scale: Parquet - columnar, typed, compressed, schema-carrying; the upgrade path from CSV when files grow or types matter.
• Small human-facing tables and interchange: CSV is fine - WITH a stated dialect (delimiter, encoding, quoting) and a data dictionary alongside (rseng-data-management).
• Domain standards first: if the field has one (NeXus for photon/ neutron science, CF-governed NetCDF in climate, community formats generally), emitting it beats inventing anything - it is what colleagues' tools already read (rseng-fair-software's I).

Formats to migrate away from when encountered: pickles as storage (unreadable outside Python, version-fragile, unsafe to load from strangers), unversioned homegrown binaries, MAT files as long-term archives, spreadsheets as databases. Flag them, explain the failure mode, offer the migration.

Metadata: the self-describing part

• Attach units, long names and fill values to every variable at write time - in code, not in a README written later. CF conventions define exactly how for NetCDF and are checkable with automated compliance checkers; run one in CI when a project's outputs claim CF compliance (rseng-ci-cd).
• Record provenance in file attributes: producing software and version, input identifiers, creation time, configuration hash - the file should testify about its own origin.
• Keep schemas versioned: when a project's file layout evolves, add a format-version attribute, and keep readers for old versions or a migration script (rseng-legacy-code discipline applied to data).

Performance engineering: chunking and compression

• Chunk to match access patterns: time-slice reads want chunks along time; map reads want spatial chunks. Wrong chunking makes reads orders of magnitude slower on large stores - decide from how the data will be READ, not written.
• Compression is usually free performance for scientific data (gzip/zstd-class codecs); test level trade-offs on real data, and prefer bit-shuffle-style filters for floats where available.
• For cloud or parallel access, chunked stores (HDF5/NetCDF-4 and their cloud-optimized descendants in the Pangeo ecosystem) enable partial and concurrent reads - the pattern behind scalable analysis (rseng-big-data-processing).

Testing format code

Round-trip tests (write, read back, compare with tolerances - rseng-numerical-accuracy), a checked-in small golden file to catch accidental format changes, and reading files produced by OTHER tools in the ecosystem as compatibility tests (rseng-testing).

Working with this skill

This skill is source-independent: its authority is the format specifications and community conventions linked below.

Learn more (verified):

• https://cfconventions.org - CF metadata conventions
• https://www.unidata.ucar.edu/software/netcdf/ - NetCDF
• https://www.hdfgroup.org/solutions/hdf5/ - HDF5
• https://parquet.apache.org - Apache Parquet
• https://www.nexusformat.org - NeXus domain format
• https://pangeo.io - Pangeo community (cloud-optimized scientific data practice)

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Related skills

Check whether any of these applies before moving on:

• rseng-big-data-processing - chunked stores enable scalable reads
• rseng-data-management - surrounding dataset practice and deposit
• rseng-fair-software - domain standards serve interoperability
• rseng-legacy-code - schema versioning and old-format readers
• rseng-numerical-accuracy - round-trip tests need float tolerances
• rseng-testing - golden-file and compatibility tests

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