 Hello everyone, I'm Colline Royaux, in general at the French Biodiversity Data e-infrastructure, PNDB. Today, I'm going to introduce our perspective on where Galaxy can help biodiversity, notably through our Essential Biodiversity Operationalization pilot. In September 2020, the fifth Global Biodiversity Outlook stated that none of the 20 IC Biodiversity targets set in 2011 by the United Nations would be fully met by January. This sad fact reminds us once again that the efforts made are insufficient and the need to follow biodiversity dynamics and produce metrics to monitor its state and guide decision making is increasingly urgent. In this objective, we identified eight fundamental needs for metrics and analyses in ecology. Biodiversity metrics need to be representative of all biodiversity levels, have diverse sensitivities to perturbations, be comparable with clear statement of computation specifics and be able to integrate data on a wide scope. Ecological analysis needs to be accessible to the widest public possible, automatable to gain time when updating a database, reproducible at any time on same and different data sets and be rigorous at each step. So to answer partially to these needs, we have essential biodiversity variables which are biological state variables, critical to describe biodiversity change accurately through time, space and biological organization. They have three key characteristics, relevance which encompasses the need for sensitivity, feasibility and convenience. EBVs are established on all biodiversity levels from genetic composition to ecosystem structure, hence our representative. In addition with the EBV concept, Kissing et al identified in 2017 a detailed workflow from observations to indicators to achieve rigorous EBV computation. With these two first concepts, we get to fill three of our needs for ecological biodiversity research and associated with the Galaxy project. Our perspective is that we can bridge the five other identified needs, comparability and integration of metrics through the use of the same formulas and tools to compute them from various data sets, accessibility and automation through facilitation to operate certain analysis methods and reproducibility through the availability of scripts and tools on web platforms. So of course we have our own Galaxy for Ecology platform, which is carried by us from the PNDB. And we have access to the usegalaxy.eu computing resources, thanks to the Fribo Galaxy team. On this instance, we identify four fully operational EBV workflows, some of which fully or partially implemented by us and some by other communities. First, the RATSEC workflow permits users to perform population genetics analysis. So producing genetic composition EBV products. Then stock and PAMPA workflows permits to produce species population and community composition EBV data products. The regional GAM workflow is dedicated to perform population and species traits analysis on butterfly phenology data. And finally, there is a workflow based on operational taxonomic units available to study community composition. Through the past year and a half, we worked on a methodical frame to ensure we get useful and useful. First thing is to start with tools that demands frequent ecological data types as input. Then to make the tools adaptable to various file formats through generalization of scripts that will be existing, well-known and time-tested. Those scripts would often require atomization and through elementary steps. So discussions with ecologists would be needed during the whole process. This methodology has been entirely applied through the implementation of the PAMPA workflow, which uses pre-processed biodiversity data to compute metrics, either at population or community levels. Then perform a generalized linear model on those metrics that test the effects of sites year and or habitat on a chosen metric. These results can then be represented through a time series plot with the last tool. So to conclude, we have the feeling that ecological and biodiversity research communities would greatly profit to use Galaxy on a regular basis and we proved that it can be carried out properly, notably through the implementation of the PAMPA workflow. We realized operative analyzation may be time costly, but it would have many benefits in the long run, such as harmonization of biodiversity assessment, time gain for future layers and adaptation of common computations, facilitation of sharing data analysis and projects between and within communities at the end of peer-reviewing of analysis protocols. Even computation, environmental footprint could be reduced and so on. Thank you very much for listening.