Abstract
Downscaled landslide experiments are an effective approach to studying complex interactions between landslide triggering factors. Working at a small scale allows seeing and measuring phenomena that cannot be quantified at a real scale with the same level of accuracy. In addition, small scale tests are useful to analyse the triggering factors separately. In this work, the dataset LISA (Landslide Investigation and Simulation Archive), containing more than 50 tests performed over 7 years using the landslide simulator of the Gap(2)Lab in the Lecco Campus of Politecnico di Milano, is presented. This dataset is structured as a database. A database is a powerful tool that allows users to interact completely and comprehensively with the stored data thanks to queries. The data acquired throughout these experiments can be exploited to test and validate landslide models and define rainfall thresholds. The data are available either through the associated database management system (DBMS), Microsoft Access, or as a set of flat comma-separated values (CSV). The entire dataset is available on the open-access repository Harvard Dataverse.