Anne Claire Mireille Fouilloux

• Fouilloux, Anne Claire Mireille & Fouilloux, Anne (2022). The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2022 update. Nucleic Acids Research (NAR). ISSN 0305-1048. doi: 10.1093/nar/gkac247.
• Fouilloux, Anne Claire Mireille & Iaquinta, Jean (2022). Earth System Model as a Service (ESMaaS). GigaScience. ISSN 2047-217X. doi: 10.5281/zenodo.4972024.

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• Fouilloux, Anne Claire & Iaquinta, Jean (2021). Galaxy and research lifecycle management technologies for earth science communities and Copernicus users in EOSC. Show summary

  The main objective of RELIANCE (https://www.reliance-project.eu/) is to provide Earth Scientists and Copernicus user communities with an innovative and interoperable service portfolio offering for an open-by-default, efficient, and crossdisciplinary research management environment supporting FAIR data principles and Open Science. Copernicus is the European Union's Earth observation programme, providing information services that draw from satellite Earth Observation and in-situ (non-space) data. This wealth of information is aimed at being exploited by everyone, for the benefit of all citizens but accessing Copernicus data is difficult and often requires advanced programming skills. By offering access to Copernicus data in Galaxy and deploying Galaxy tools for analyzing and creating advanced workflows, we believe it will democratize the usage of such data and facilitate cross-disciplinary research. RELIANCE service ecosystem (Research Objects, Data Cubes and AI-based Text Mining) will be "connected" to Galaxy to facilitate the re-use of generated Research Objects from Galaxy. During GCC2021, we will present the current status and the roadmap.

• Fouilloux, Anne Claire & Steinbach, Peter (2020). Teaching ML in Compact Courses.
• Fouilloux, Anne Claire (2020). Visualize Climate data with Panoply netCDF viewer. Show summary

  The practical aims at familiarzing you with the Panoply Galaxy interactive environment. Panoply is among the most popular tool to visualize geo-referenced data stored in Network Common Data Form (netCDF). It provides a graphical interface for inspecting (show metadata) and visualizing netCDF data. It supports many features to customize your plots and we will introduce some of them in this lesson.

• Fouilloux, Anne Claire (2020). Getting your hands-on climate data (Galaxy Training Materials). Show summary

  The e-learning aims at familiarzing you with Climate Science and the terminology used by climate scientists. The target audience is not a climate scientist but anyone interested in learning about climate.

• Fouilloux, Anne Claire (2020). K3D Jupyter notebook extension for 3D visualization.
• Fouilloux, Anne Claire (2020). EOSC-Nordic & NICEST2 NeIC projects within INES context.
• Fouilloux, Anne Claire; Hasan, Adil; Lukkarinen, Ari & Struthers, Hamish (2020). Nordic climate scientists are turning to Open Science.
• Hasan, Adil; Fouilloux, Anne Claire & Jacquemot, Christine (2020). Integrating maDMP with the data management process. Zenodo. Show summary

  he data management process for a research project covers the collection, storage, transformation, analysis and archiving or deletion of the data. Each of these stages can involve some complex and detailed steps. Projects in the same discipline may have very similar, or even the same, series of steps in a given stage. For example, more than one project may make use of the same multi-purpose detector. For each project the transformation from the raw data into more physical quantities (such as pulse signals from a detector into three-dimensional coordinates) could be common. If one project were able to define such a workflow and include it as part of their DMP, other projects would be able to reuse it. Capturing these workflows in the DMP would more accurately reflect the data management process and provide some value to follow-up, or related projects that have similar workflows and which would be able to reuse these workflows. The task we set ourselves for the hackathon was to take some specific workflows from a portion of the data management process for the Climate community in the EOSC-Nordic project and see how we could capture the workflow within the maDMP schema. This report is a summary of work done by the Something team at the RDA Hackathon on machine-actionable Data Management Plans that took place between 27th and 29th May 2020

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