A phenomenological interpretation of the slope factors and lanslide mechanism represents the first stage for the assessment of landslide hazard at the slope scale. This requires processing, analysing and integrating a large set of multidisciplinary and heterogeneous data, obtained through diverse activities, among which: geological and geomorphological studies, geotechnical investigations and monitoring, topographic and structural damage surveys. The integration of such a variety of multisource data, to build up a sound conceptual model of the slope, can be particularly challenging, especially in geohydromechanical contexts characterised by a great spatial variability of soil properties and complex hydraulic boundary conditions, such as in the case of slopes composed of turbiditic formations. This paper presents a new methodological approach for the study of landslide hazard at the slope scale, based on the combined use of an open-source GIS platform and an in-house developed dashboard for the interactive visualisation and analysis of geotechnical laboratory data. The details of the GIS project and the potentiality of the data-analysis dashboard are described, highlighting the interoperability between the two digital tools. The proposed methodology is applied to a pilot site, the Pianello area in Bovino, in the souhteastern Apennines, a widely investigated hillslope composed of tectonised clayey turbidite, hosting a complex basin of slow-moving landslidesSince the 1980s and to date, extensive survey and monitoring campaigns have been carried out to characterize the Pianello hillslope and to interpret the existing landslide mechanisms, collecting a large but heterogeneous database. This study presents the results of the integration of the whole set of geotechnical, geophysical, lithological, geomorphological and monitoring data, as well as data concerning damage on buildings, for the Pianello area, resulting in a reliable conceptual model of the landslide processes, whose activity is found to be at least partly climate driven. The employed workflow comprises, alongside with traditional desk studies, the use of the open-source GIS platform QGIS and an in-house developed interactive dashboard for the analysis of geotechnical laboratory and monitoring data, entirely written in Python.