Spectroscopy and Analytical Chemistry Formats

Reviewed: 2026-07-23 Executable scope: No spectroscopy-native parser is bundled. General CSV/TSV/JSON/NumPy/HDF5 inspectors apply only when a file is truly one of those registered formats and do not add spectroscopy semantics.

Capability boundary

Unknown formats fail closed. Directory-based acquisitions are rejected by the regular-file CLIs. No archive or compressed stream is unpacked.

mzML and related mass-spectrometry formats

HUPO-PSI identifies mzML 1.1.0 as the long-term stable format; its index schema and controlled vocabulary continue to receive compatible updates. mzML is XML with encoded binary arrays and controlled-vocabulary metadata. A generic XML parser is not sufficient.

Use pinned pymzML, Pyteomics, OpenMS, or ProteoWizard tooling and inspect:

• schema/version, controlled-vocabulary terms, source files, checksums, and conversion software;
• run/instrument configuration, polarity, scan modes, MS levels, isolation, activation, and data processing;
• spectrum/chromatogram counts, retention/mobility time, m/z and intensity array lengths, precision, compression, and units;
• profile versus centroid data, TIC/BPC, calibration, lock mass, blanks, pooled QC, standards, carryover, drift, and batch order; and
• truncated scans, empty arrays, non-finite values, and metadata consistency.

Do not describe mzXML, mzData, mzMLb, or vendor RAW as equivalent to mzML. Conversion can alter metadata, precision, centroiding, and compression; record the converter/version/options and retain the original.

JCAMP-DX

IUPAC describes JCAMP-DX as a family of standards for spectral data exchange. It has technique- and version-specific specifications (IR, NMR, MS, IMS, and others); active core development stopped in 2006, although the format remains in use.

Before parsing, identify the technique and specification/version. Validate:

• label/value records and required metadata;
• X/Y units, first/last X, point count, spacing, factors, and encoded numeric representation;
• NTUPLES versus simpler XY forms;
• page/block boundaries and compound/instrument identifiers; and
• whether data are absorbance, transmittance, counts, complex NMR, peaks, or continuous spectra.

Metadata and comments are untrusted and should not be copied into a report. The generic tabular scanner is not a JCAMP parser.

NMR data

.fid, Bruker directory layouts, Varian/Agilent layouts, processed spectra, and NMR exchange files require producer-aware tooling such as nmrglue. Record:

• vendor/software/version and complete acquisition directory;
• nucleus, field strength, spectral width, dwell time, point count, quadrature, digital filter, scans, temperature, pulse sequence, and reference;
• raw FID versus processed spectrum, apodization, zero filling, Fourier transform, phase, baseline, referencing, and solvent suppression;
• dimensional axes/units and whether data are real, imaginary, magnitude, or complex; and
• sample preparation, concentration, pH, replicates, and batch/order.

Peak picking, integration, baseline correction, phase correction, alignment, binning, and normalization are transformations. Preserve raw data and report parameter sensitivity; do not apply them automatically.

Optical, vibrational, and diffraction spectra

SPC, OPUS, WDF, SPE, instrument .raw, .dat, and text exports are producer/variant dependent. Confirm:

• physical X axis (wavelength, wavenumber, energy, angle, time) and units;
• Y quantity (counts, intensity, absorbance, transmittance, reflectance) and calibration;
• point order/spacing, detector/channel, exposure/accumulations, resolution, slit/grating/laser/source, and polarization;
• background/reference/dark correction and all processing already applied; and
• maps, time series, replicate spectra, and spatial coordinates.

For XRD, crystallographic CIF/MTZ/HKL are also reference-only and need crystallography-aware validation. A .cif suffix is ambiguous between small-molecule CIF and PDBx/mmCIF.

Chromatography and thermal/electrochemical exports

Generic CSV/TSV can contain retention time, temperature, potential, wavelength, or another independent axis. The general scripts can profile the table only after the data dictionary confirms:

• axis and signal columns, units, ordering, spacing, and replicate layout;
• blanks, calibration standards, internal standards, dilution factors, injection order, batch, and sample identifiers;
• LOD/LOQ, saturation, censoring qualifiers, and negative/zero handling; and
• whether peaks/integrals are raw, manually edited, or software-derived.

Do not infer an axis from monotonic values or a column name. Do not automatically smooth, baseline-correct, align, integrate, normalize, subtract blanks, or delete peaks.

Safe bounded tabular workflow

For an approved values-only export:

python scripts/tabular_profile.py spectrum.csv \
  --root /approved/project \
  --max-rows 100000

python scripts/missingness_leakage_audit.py spectrum.csv \
  --root /approved/project \
  --group-column sample_group \
  --entity-column sample_id \
  --split-column split \
  --time-column acquisition_time

python scripts/distribution_sensitivity.py spectrum.csv \
  --root /approved/project \
  --column intensity

Use only pseudonymous column roles in shared commands/logs. The outputs contain aggregates and tokens, not spectra or identifiers.

Analytical EDA rigor

1. Define the independent unit: scan, injection, spectrum, sample, batch, subject, instrument, site, or experiment.
2. Preserve raw acquisition files and processing audit trails.
3. Record calibration, units, standards, blanks, internal standards, acquisition order, maintenance, software, and method versions.
4. Keep non-detects, below-LOQ values, saturation, missing scans, failed QC, and true zeros distinct. Preserve qualifier and limit fields.
5. Compare raw and processed summaries and sensitivity to baseline, smoothing, peak picking, alignment, integration, normalization, and transformations.
6. Investigate outliers against calibration, instrument state, carryover, and sample handling; do not delete automatically.
7. Split independent samples/batches/time before learned preprocessing. Never fit normalization or feature selection on test data.
8. Account for repeated spectra, technical replicates, correlated wavelengths/ peaks, and many comparisons.
9. Label discovered peaks/patterns as exploratory and confirm independently.
10. Do not make identity, purity, mechanism, exposure, diagnostic, or causal claims from EDA alone.

Detection limits and censoring

EPA guidance treats non-detects/over-detects as censored observations carrying partial information and recommends preserving detection condition and limit type rather than forcing a numeric result. Apply the same principle to instrumental assays:

• keep measured value, qualifier, limit type, and limit value in distinct fields;
• do not replace censored values automatically with zero, LOD/2, or LOQ;
• summarize the censoring fraction by group/batch/time;
• choose a model appropriate to censoring and scientific design; and
• report sensitivity to plausible assumptions.

Authoritative sources

All links accessed 2026-07-23.

• HUPO-PSI, mzML specification/status (mzML 1.1.0 long-term stable; current schema/CV links and 2026 IM-MS/DIA proposal status).
• HUPO-PSI, mzML GitHub specification repository.
• IUPAC, JCAMP-DX digital standard family (page dated 2021-08-03; finalized technique-specific standards).
• IUPAC, JCAMP-DX 5.01 recommendation.
• nmrglue, current documentation.
• US EPA, Detection Limits Best Practices Guide, dated August 2025.
• NIST/SEMATECH, Exploratory Data Analysis.
• FDA/ICH E9(R1), estimands and sensitivity analysis, final guidance May 2021.