Consumer preference data for black coffee

The dataset provided here contains physical, chemical, and consumer preference data for 118 individual consumers who each tasted 27 distinct coffees prepared with precisely controlled brewing conditions, yielding a total of 3,186 individual tastings of black coffee.  Physical measurements include the temperature, total dissolved solids, and percent extraction of the brewed coffee; chemical measurements include the pH and titratable acidity of the brewed coffee; and the consumer preference measurements include hedonic liking, just-about-right assessments of beverage temperature, flavor intensity, mouthfeel, and acidity, and purchase intent.  A total of 48 variables are quantified in a spreadsheet with 3,168 rows representing each individual consumer's assessment of each coffee.  The dataset is associated with two papers: (1) \"Consumer Preferences for Black Coffee are Spread Over a Wide Range of Brew Strengths and Extraction yields,\" by Cotter, Ristenpart, & Guinard, Journal of Food S..., The data presented here are drawn from a large study that afforded an opportunity to assess consumer preferences for coffee-tasting temperature. Specifically, we used a 3x3x3 factorial design to determine how the brew strength, extraction yield, and brew temperature affected the sensory attributes and consumer preferences for drip-brewed black coffee. Three specific brew temperatures of 87, 90, and 93°C were tested, with great care taken to adjust the grind size and flow rate such that the final brew strength and extraction yield were held constant despite the different brew temperatures. 
Full details regarding the type of coffee, water chemistry, and brewing protocols are available in Cotter et al., Journal of Food Science, 2021.  In brief, a medium-roast washed coffee from Honduras was used for all trials, using water with mineral content and pH recommended by the Specialty Coffee Association.  Coffees were brewed using Curtis ThermoPro Single 1 Gallon Coffee Brewers, using one of th..., The dataset consists of one large excel spreadsheet, which may be opened with Microsoft Excel or Google Sheets.  Each row represents the data collected for one individual tasting by a panelist; all personal identifiers have been removed.  The first row contains the 48 variable names.  The variables are defined as follows:

Judge:  numerical identifier of an individual person.  Ranges from 1 to 118.
Cluster: numerical identifier for which consumer preference segmentation cluster the individual judge was identified as belonging to.  Either 1 or 2.  (See Cotter et al. 2021).
Week: identifies which week the tasting of that coffee occurred. Either 1, 2, or 3 for first, second, or third weeks respectively.
Session Number: identifies which of the 18 unique tasting sessions this tasting occurred at.  Ranges from 1 to 18 (with six tastings per week over three weeks).
Position: identifies the order in which this specific coffee was sampled within a session.  Range from 1 to 10 (for first to last ...