Seed Data

Semilattice assumes column headers are questions or propositions: pieces of text posed to people who can respond with an answer. For example, “What is your favourite colour?” is a question while “You believe reality is…” is a proposition.

Questions can’t assume the responder has any knowledge of the other questions in the dataset. For example, the question “How strongly do you feel about your answer to the last question?” will not work because with simulated respondents there isn’t an equivalent of a real-world survey’s last question. Similarly, grid questions must be reformatted so that the question is included with each column of answers.

Answer options cannot refer to the question’s other answer options. For example, the answer option “None of the above” is invalid because its meaning depends on the other answer options.

Survey, poll, and questionnaire datasets often record questions and answers as descriptors, identifiers, or codes requiring lookup in data dictionaries. Semilattice only accept a single .csv, so questions and answers have to be decoded into human-readable strings.

Mixing data from different samples is not recommended. Semilattice assumes seed data come from a single survey, poll, or questionnaire.

Mixing answers from different people is not recommended. Semilattice assumes all the answers in a row come from the same person.

The set of unique values in a column define the answer options for the question in that column. For example, the unique values under the question header “What is your favourite colour?” may be: “Red”, “Green”, “Blue”, “Yellow”, “Purple”, “Orange”, “Teal”, “Pink”, “Brown”, “Indigo”.

Questions which were originally posed as single option multiple-choice questions are recommended, but if necessary other, compatible types of questions can be reformatted. For example, multiple selection questions (e.g. “Choose all that apply…”) can be reformatted into one binary question for each selection option (e.g. “Do you do X?”, “Do you do Y?”, …). Or you can group and recode respondents’ answers to free text questions to make a single option multiple-choice question. Caution is advised though: the more you reformat, the more your seed data will diverge from reality.

The order of the question columns in your seed data has no effect. Questions will be used in various ways, in various orders.

Answer options will be presented in random order by default. Answer options with semantic order (e.g. “Strongly Agree” to “Strongly Disagree”) are perfectly valid, but answer options which assume an order (e.g. “None of the above”) are not. Answer options like “None of the above” should be reformatted to stand alone, e.g. “None”.

You can filter large datasets down to specific segments, subsets of questions, or the right number of respondents for Semilattice. However, just like with a real-world survey, heavy filtering of a dataset can reduce the quality of the resultant sample and can lead to lower accuracy Populations in Semilattice.