This dataset contains the spectral data acquired on waste wood samples using a FT-NIR spectrophotometer (Q-Interline A/S, Tølløse, Denmark) provided with the patented spiral sampler (Spiral Sampler, Q-Interline A/S, Tølløse, Denmark). The waste wood samples have been collected in a panel board company located in the Northern part of Italy during two days of sampling (February 18-19, 2020). In detail, 64 samples (16 lots x 4 samples from each lot) were obtained; later each sample has been split into two replicates for a total of 128 samples. Because of an unfortunate computer error (i.e. the computer froze without saving the collected data) only realized after arriving back at the University, the spectral data of two sample replicates have not been stored. Hence, the final dataset consists of 26192 observations and 1091 wavenumbers (around 210 NIR scans per sample replicate). The sample has been analysed with a particle size of 5 mm. The CSV file contains the following information in the columns: Sample code: it is reporting the sample code where S1 is the number of lot, the successive number is the number of subsample and the last number the NIR replicate. E.g. S01-01_122: lot number 1, subsample number 01, NIR replicate number 122. Please note that we have also letter ‘B’ when we are looking at the second subsample replicate. Lot: number of lot to which the sample belongs (from 1 to 16). Subsample: number 1, 7, 13 or 19 indicating the four subsamples; Replicate: number 1 or 2 indicating first or second replicate. Measurement: the number of the NIR measurement. Spectral data: absorbance values for each sample from 3595.05 cm-1 to 12004.07 cm-1. The aim behind this dataset is to provide information about the frequency of sampling and number of replicates and scans to perform for describing the waste wood variability (WP1 of WoodSpec project). A correct sampling procedure is fundamental to guarantee an accurate and successful use of a NIR sensor into real industrial applications and improve the waste wood management, especially when dealing with heterogeneous material. Funding: The project leading to this application has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 838560. Terms of use: These data are provided "as is", without any warranties of any kind. The data are provided under the Creative Commons Attribution 4.0 International license.