Fractionatiedata

Fractionatiedata is a structured data representation used to capture results from fractionation experiments, where a sample is separated into discrete fractions and measured across each fraction. The term is a composite of fractionation and data. In practice, fractionatiedata supports documenting the overall experiment, the properties of each fraction, and the relationships between fractions and their source material.

Core elements include a fractions collection; each fraction has an identifier, boundaries (start and end coordinates such as volume, time, or elution fraction number), and measured attributes (e.g., concentration, absorbance, activity, spectral data). The data model includes sample metadata (sample_id, preparation method), instrument and protocol metadata (instrument_id, method, conditions), and quality flags.

Formats for fractionatiedata can include JSON, CSV with a per-fraction row structure, or hierarchical formats like HDF5. It supports linking to external data (e.g., spectra files) and metadata standards for interoperability. A minimal schema would include fields for sample_id, experiment_date, method, and an array of fractions with id, boundaries, and measurements.

Applications of fractionatiedata include analyzing elution or separation profiles, quantifying component distribution across fractions, comparing runs, and supporting reproducibility. Common analyses encompass peak detection, profile fitting, normalization, and cross-fraction comparisons.

Limitations and considerations include the accuracy of fraction boundaries, as missing or misaligned fractions can distort interpretation. Data provenance and versioning are important for reproducibility. The term fractionatiedata is used in some software and research contexts as a generic model for fraction-based measurements.