Résumé
Stock assessment models are developed to provide scientific advice to managers about exploited populations. Stock assessment software are complex and advanced technical skills are required to develop the models. Producing output becomes time-intensive and even more complex as thousands of simulations must be run on supercomputers in order to include the multiple sources of uncertainty in assessment results. As very few stock assessment participants have the specific technical skills required to reproduce these outputs, our aim has been to develop a Virtual Research Environment (VRE) that enables any user to easily parameterize and execute various steps of the stock assessment workflow using SS3 (a widely-used statistical catch-at-age model). We will repackage SS3 codes used for large pelagic species and provided by the Indian Ocean Tuna Commission and their consultants so that they can be parameterized, executed and edited online by anybody from a simple web page, with standardized data outputs. The VRE will provide various collaborative web services, including: (i) a workspace to share documents or data, (ii) webpages or an RStudio server to process data online, and (iii) an automated reporting service to dynamically generate documents to package these results. Here, we will show a mock-up of the VRE, using the last stock assessment of swordfish (SWO) as an example. Using an R-shiny application, we will explain the procedure of inputting new data, changing parameters, and quickly and automatically viewing the results of these changes on the graphical interface as well as through the automated reporting service. A collaborative environment such as the VRE uses simple tools to enable the storage and access of the data and source codes necessary to replicate past results or to try new parameterizations of the model. Increasing access to this complex model will bring more transparency and collaboration within working groups by providing ?non-modelers? with a possibility to test hypotheses for the stock assessment. This will also increase the number of users of various levels of expertise: from experts, to managers, to even wider audiences with the potential applications of these tools to serious games.