Open Science Behaviour Dataset with Synthetic Data and Monte Carlo Validation

This dataset supports a study on modelling open science behaviour using a bootstrap-based Monte Carlo approach. It includes a cleaned dataset derived from a survey of researchers affiliated with Spanish institutions, a synthetic dataset generated through bootstrap resampling, and comparative statistical outputs validating the structural consistency between real and synthetic data. The dataset focuses on behavioural dimensions related to open science practices, including data deposit, data reuse, transparency attitudes, peer review perceptions, and conflict perception. A composite index measuring overall open science attitude is also included. Additionally, the repository contains derived datasets used to generate the figures presented in the associated publication, ensuring transparency and reproducibility. This resource may support further research in information behaviour, open science adoption, behavioural modelling, reproducibility, and synthetic data generation.