Open resources for psychometric research and teaching.

Application developed at the lab to simulate realistic, flexible and reproducible datasets for teaching and research in the social, behavioural and health sciences. Every run produces not only the data, but a complete package of resources designed to make the process transparent and reusable: a detailed report listing the parameters, models and population characteristics used; a directed acyclic graph (DAG) that visually represents the generative process and turns the simulation itself into a teaching tool; and exportable configurations that let you reproduce, modify or share any scenario.

Open platform to design, run and validate AI-assisted qualitative coding workflows. Lets you compose visual workflows that combine generative models, deductive and inductive coding, human-in-the-loop review and intercoder agreement metrics. Includes a catalogue of typed nodes, canonical templates — meta-prompting, intercoder validation, inductive exploration, etc. — and a bank of reusable models, prompts, codebooks and corpora. Every run is recorded as traceable, reproducible validity evidence.