The human factor: results of a small‐angle scattering data analysis round robin

• Published in: Journal of applied crystallography Vol. 56; no. 6; pp. 1618 - 1629
• Main Authors: Pauw, Brian R., Smales, Glen J., Anker, Andy S., Annadurai, Venkatasamy, Balazs, Daniel M., Bienert, Ralf, Bouwman, Wim G., Breßler, Ingo, Breternitz, Joachim, Brok, Erik S., Bryant, Gary, Clulow, Andrew J., Crater, Erin R., De Geuser, Frédéric, Del Giudice, Alessandra, Deumer, Jérôme, Disch, Sabrina, Dutt, Shankar, Frank, Kilian, Fratini, Emiliano, Garcia, Paulo R. A. F., Gilbert, Elliot P., Hahn, Marc B., Hallett, James, Hohenschutz, Max, Hollamby, Martin, Huband, Steven, Ilavsky, Jan, Jochum, Johanna K., Juelsholt, Mikkel, Mansel, Bradley W., Penttilä, Paavo, Pittkowski, Rebecca K., Portale, Giuseppe, Pozzo, Lilo D., Rochels, Leonhard, Rosalie, Julian M., Saloga, Patrick E. J., Seibt, Susanne, Smith, Andrew J., Smith, Gregory N., Spiering, Glenn A., Stawski, Tomasz M., Taché, Olivier, Thünemann, Andreas F., Toth, Kristof, Whitten, Andrew E., Wuttke, Joachim
• Format: Journal Article
• Language: English
• Published: 5 Abbey Square, Chester, Cheshire CH1 2HU, England International Union of Crystallography 01-12-2023; Blackwell Publishing Ltd
• Subjects: Data analysis; Data Analysis, Statistics and Probability; Datasets; Dilution; Dispersions; Human factors; interlaboratory comparability; nanomaterials; nanostructure quantification; Physics; round robins; Scattering; small‐angle scattering; Structure factor; nanomaterials; data analysis; small-angle scattering; round robins; interlaboratory comparability; nanostructure quantification
• ISSN: 1600-5767; 0021-8898; 1600-5767
• DOI: 10.1107/S1600576723008324

A round‐robin study has been carried out to estimate the impact of the human element in small‐angle scattering data analysis. Four corrected datasets were provided to participants ready for analysis. All datasets were measured on samples containing spherical scatterers, with two datasets in dilute dispersions and two from powders. Most of the 46 participants correctly identified the number of populations in the dilute dispersions, with half of the population mean entries within 1.5% and half of the population width entries within 40%. Due to the added complexity of the structure factor, far fewer people submitted answers on the powder datasets. For those that did, half of the entries for the means and widths were within 44 and 86%, respectively. This round‐robin experiment highlights several causes for the discrepancies, for which solutions are proposed.
A data‐analysis round robin was performed using four real‐world datasets to quantify the role of the human factor in analysis; the 46 responses show that the analyses by different researchers and laboratories may not be directly comparable, with large reporting inconsistencies in distribution widths and volume fractions. Several underlying causes for these inconsistencies are highlighted that can be addressed by the community.