Geographic data are increasingly readily available for agricultural and environmental applications, as evidenced by the increasing use of satellite imagery and drones for image capture in agriculture and environmental management and the ubiquity of GPS technology in modern data collection tools. Professionals may also have access to vast amounts of spatial information through their own institutions (public or private) without having the necessary knowledge and skills to process it. Therefore, agriculture and environmental professionals, among others, must be able to acquire these new skills to extract and explore these important resources in current decision-making processes. To be able to meet these challenges, the user does not absolutely need to be an expert in GIS or statistics, but must have sufficient experience to solve common practical problems. The OpenSpat project aims to improve the skills of these professionals in this regard. It helps them use the open source tools available to extract and analyze spatial data in a way that is relevant to their professional activity. This project is being developed by three partners: the University of Lisbon, which has solid experience in teaching courses on GIS and spatial data analysis with R software, SupAgro Montpellier, which has skills in statistical modelling, experience in the creation of MOOC and has technical and logistical support for the project (including a video studio), and the University of Liège, which has experience in the organisation and management of master's degree courses in applied statistics and which has a department dedicated to higher education (IFRES) that can provide the necessary support during the construction and evaluation of the training modules. The first year was devoted to the creation of training materials. The many exchanges, whether via online communication tools or transnational meetings, made it possible to share pedagogical practices, meet local actors and integrate their constraints into the project, determine the final content of the training and the tools implemented. During the second year, the curriculum thus created was tested on a panel of students selected from among the 3 partners. The effectiveness of the selected learning techniques (video clips, blended learning) was evaluated and analyzed to refine the learning activities of the third year. The learning activities in year 3, corresponding to 6 ECTS of intensive courses on spatial data analysis with open tools, took place in Belgium, but will be transferable to the partners' institutions after the project. The activities take the form of an introductory MOOC followed by blended learning activities, with a maximum of two weeks of face-to-face activities, and are based on teaching materials created during the project: syllabus, presentation materials, data sets, exercises and computer scripts. In the second year, the first results of the follow-up of the project's learning activities were presented during the UseR2017 conference in Brussels, thus ensuring wide international publicity for the project. For target groups and stakeholders (public or private life sciences companies needing expertise in spatial data analysis), the project fills a gap in the training offer, allowing them to acquire key competences in spatial data analysis in an organisational design specially adapted to their needs and constraints and thus to increase the skills in applied statistics for spatial data analysis on the labour market and the high demand for spatial data analysis workers. In addition to the creation of the learning modules themselves and their availability via the European Valor/PRP platform, the project has enabled partner institutions to come closer together and new Erasmus+ agreements to be signed, aimed at ensuring the sustainability of the education offer thus created. At the end of the project, the training module based on the materials created during the project will be delivered each year alternately in each partner institution, starting with the University of Lisbon in 2019. The project also created an emulation between the project partners in the fields of data analysis and innovative pedagogy, which allowed the dissemination of new practices between partner institutions, such as new tools for active pedagogy, sharing, script editing, etc. Thanks to the experience in transnational education, the partners involved are now studying the long-term feasibility of a larger-scale transnational programme, such as a European Master's degree.