Different seriation techniques require different types of data. The data type for a feature can be set on the Features table
Measured Data - can be any numerical value including integers (-5, 1, 3, 0, etc.) and fractions expressed as decimals (1.3, -0.43, -3.14159, 2.71828, etc.). Measured data is assumed to reflect a measurement (height, width, length, distance, weight, count, ratio, etc.) of a feature. OptiPath will try to order the artifacts according to the measures of their features (smallest to largest or vice versa) in creating a seriation.
Ranked Data - can be used to categorize data where the ordering of the categories is important. Depending upon the metric used, OptiPath will try to preserve the order of the categories (smallest to largest or vice versa) in creating a seriation.
Classed Data - can be any alphanumeric value ("red", "-78", "large", "3.14159", "0", "absent", "dentate", etc.). Classed are used to identify a feature without implying any innate ordinal value. Using classed data, OptiPath will try to sort artifacts to preserve temporal proximity of features of the same class (with the same nominal value) but will make no attempt to sort or order the classes. For example, with nominal feature values of "red", "blue" and "green", OptiPath would try to group all of the "red" artifacts together, and similarly the "blue" and "green", but would be indifferent between an ordering that put "red" before "blue" before "green" and one that put "blue" before "red" before "green". The same would hold true if you were to name your classes "1", "2", "3" and "4" in which case OptiPath would be indifferent between 1-2-3-4 and 4-1-3-2.