Sensometric data sets are made available here to facilitate the development of new statistical methods for data analysis.

If using any of the data sets provided, please cite the work(s) indicated in the citation request.

Data sets currently available:

• Brown Bread (Data set for the Sensometrics 2016 Data Analysis Workshop)
  Source: Dr. C. J. Findlay, Compusense Inc., Canada (April 2016)
  Description: 570 consumers each evaluated 6 brown breads on the 9-point hedonic scale in a 16-present-6 sensory-informed balanced incomplete block design. Missing data (denoted NA) appear by design. Refer to the publication by Franczak et al. (2015) for further details. The file is in CSV format.
  Citation request: Franczak, B. C., Browne, R. P., McNicholas, P. D., & Findlay, C. J. (2015). Product selection for liking studies: The sensory informed design. Food Quality and Preference, 44, 36-43. http://dx.doi.org/10.1016/j.foodqual.2015.02.015
  
  
• Fried Mozarella Cheese Sticks
  Source: Dr. C. J. Findlay, Compusense Inc., Canada (July 2014)
  Description: 161 consumers evaluated 8 fried Mozarella cheese sticks for overall liking, as well as liking for appearance, flavor, and texture. There are some missing data. Descriptive analysis was conducted on the same products by a trained panel; panel mean values for 37 attributes are given. The file is in XLS format.
  Citation request: Meullenet, J.-F., Xiong, R., & Findlay, C. J. (2007). Multivariate and Probabilistic Analyses of Sensory Science Problems. Ames, IA, USA: Blackwell Press.
  
  
• Muscadine Grape Juices
  Source: Dr. C. J. Findlay, Compusense Inc., Canada (July 2014)
  Description: 61 consumers evaluated 10 Muscadine grape juices for overall liking, as well as liking for appearance, aroma, color, and flavor. Descriptive analysis was conducted on the same products by a trained panel; panel mean values for 15 attributes are given. The file is in XLS format.
  Citation request: Meullenet, J.-F., Xiong, R., & Findlay, C. J. (2007). Multivariate and Probabilistic Analyses of Sensory Science Problems. Ames, IA, USA: Blackwell Press.
  
  
• White Corn Tortilla Chips
  Source: Dr. C. J. Findlay, Compusense Inc., Canada (July 2014)
  Description: 80 consumers evaluated 11 white corn tortilla chips for overall liking, appearance liking, and flavor liking, as well as for saltiness on a 5-point Just-About-Right scale, and for Purchase Intent. There are some missing data. Descriptive analysis was conducted on the same products by a trained panel; panel mean values for 37 attributes are given. The file is in XLS format.
  Citation request: Meullenet, J.-F., Xiong, R., & Findlay, C. J. (2007). Multivariate and Probabilistic Analyses of Sensory Science Problems. Ames, IA, USA: Blackwell Press.
  
  
• Peas
  Source: Prof. P. B. Brockhoff, Danish Technical University, Denmark (July 2014)
  Description:12 trained assessors evaluated 16 pea products for 13 sensory attributes in 3 replicates. The data set contains some imputed values. The file is in XLS format.
  Citation request: Naes, T., Brockhoff, P. B., & Tomic, O. (2011). Detecting and Studying Sensory Differences and Similarities between Products. In: Statistics for Sensory and Consumer Science (pp. 47-66). West Sussex, UK: John Wiley & Sons.
  
  

To contribute your data sets to the Sensometric Society, please contact the website administrator. You should hold the rights to permit the data set to be distributed publicly, and indicate a description of the file and a citation request, where applicable.

Links to sensory data sets hosted on external pages:

Varela Tomasco, P. & Ares, G. (Eds). (2014). Novel Techniques in Sensory Characterization and Consumer Profiling. Boca Raton: Taylor and Francis. http://www.crcpress.com/product/isbn/9781466566293

R packages containing sensory data:

lmerTest contains the data set ham.

ordinal contains the data sets soup, wine.

reshape contains the data set french_fries.

SensoMineR contains the data sets chocolates, cocktail, cream_id, cream_signa, napping, perfume, perfume_fcp, perfume_ideal, smoothies.

sensory contains the data sets bbread, wbread.

tempR contains the data sets bars, syrah.