ATMODAT
ATMODAT is a recommendations framework for making atmospheric research data more FAIR. It focuses on the metadata, identifiers, file formats, and documentation needed so that observational and modeling datasets remain interpretable beyond the original project that produced them.
Why it matters
Atmospheric datasets are often technically readable but still hard to reuse because key context is missing: sensor setup, calibration history, variable definitions, coordinate systems, processing steps, or license information. ATMODAT addresses that gap by defining what should be documented alongside the data itself.
Core expectations
- Persistent identifiers: People, institutions, datasets, and referenced resources should use stable identifiers such as ORCID, ROR, or DOI where possible.
- Structured metadata: Temporal coverage, spatial reference, variables, units, and methodological context should be described in a machine-readable way.
- Controlled vocabularies: Keywords and variable descriptions should use shared vocabularies where possible to improve interoperability.
- Clear licensing: Reuse conditions should be stated explicitly and ideally machine readable.
File-format guidance
ATMODAT strongly aligns with self-describing scientific data formats such as netCDF, including clear coordinate definitions, rich variable attributes, and standard conventions such as CF conventions. In practice, that means datasets should expose time, space, and variable metadata directly in the file rather than leaving interpretation to a PDF or README alone.
Relation to FAIR and provenance
ATMODAT is best understood as an implementation layer for FAIR atmospheric data. It turns general principles into concrete documentation requirements and encourages stronger provenance for derived products and workflow outputs.
In this garden
ATMODAT connects the open-science branch to climate-data practice:
- Metadata explains the descriptive layer.
- FAIR provides the broader principles.
- UC2 data standard shows a project-oriented standardization effort.
- common data language and netCDF describe file-level interoperability.
See also: FAIR, Metadata, Provenance, UC2 data standard, netCDF, CF conventions, MOC Open Science Data and Knowledge Graphs