Quick Introduction to the Spectral Dictionary

The Spectral Discipline Dictionary is used to provide metadata that describes how a light spectrum is presented in a data object. This guide defines the terminology used in the Spectral Dictionary and provides a brief overview of the various methods available for defining the relevant metadata in your product labels.

Preliminaries

First off, note that the Spectral Dictionary is designed only for light spectra. More specifically, it is designed to describe wavelength, frequency, and wavenumber spectra. It does not describe mass spectra, time-of-flight spectra, or any spectra that are not the direct result of gathering photons.

Further, the Spectral Dictionary can only handle spectra that are in one of the following data structures:

• A table in which each row of the table contains a complete spectrum ("Tabulated Spectra")
• A table in which each row of the table contains a single point in a spectrum, and the entire table comprises a single spectrum ("1D Spectrum")
• An image array (specifically, an <Array_2D_Spectrum> object) , where either the axes of the array are aligned with the spectral dimensions, or the array contains an image which presents a recorded spectrum
• A stack of images (<Array_3D_Spectrum>), where each plane is a 2D spectrum (as in the previous bullet)

If you have spectral data that doesn't fit those models, talk to your PDS Node consultant about the best course of action.

Terminology

The bulk of the Spectral Dictionary is concerned with defining the quantization of the spectrum - in other words, what range of wavelengths (or frequencies, or wavenumbers, as appropriate) is represented by each pixel (or row, or column) along the spectral dimension of the data structure.

Spectral "Bins"

The term binning is used to refer to the spectral quantization throughout the Spectral Dictionary, irrespective of data structure. The bin corresponds to the spectral range associate with a single point:

• In tabulated spectra, individual fields represent bins.
• In 1D spectra, each row is a bin.
• In 2D spectra, each pixel along the spectral axis is a bin.
• In 3D spectra, each pixel along the spectral axis (which corresponds to a plane in the perpendicular axes) is a bin

These data structure bins may or may not correspond to the bins of the original detector, either because of re-binning of digital data or digitization of analog data. Regardless, the relationship between detector bins and data structure bins should be well-documented, and in every case when the Spectral Dictionary refers to "bins", it is the data structure bins that are intended.