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4 materials found

Contributors: Hélène Chiapello 


FAIR data - Module 4 (share and publish data)

Partager et diffuser les données. Le cadre juridique, les entrepôts et les licences sur les données

Scientific topics: Data management, Biology, Bioinformatics

Keywords: data sharing, Data publishing, legal framework, data warehouse, licensing, data reuse

Resource type: Slides

FAIR data - Module 4 (share and publish data) https://tess.elixir-europe.org/materials/fair-data-module-4-share-and-publish-data Partager et diffuser les données. Le cadre juridique, les entrepôts et les licences sur les données Hélène Chiapello Thomas Denecker Jean-François Dufayard Gautier Sarah Julien Seiler Data management Biology Bioinformatics data sharing, Data publishing, legal framework, data warehouse, licensing, data reuse Biologists bioinformaticians Biomedical researchers
FAIR data - Module 1 (research data)

Research data and their centrality in the research process. This material is mostly in French.

Scientific topics: Biology, Bioinformatics, FAIR data, Open science

Keywords: metadata, Data Life Cycle, Reproducibility, Data management plan

Resource type: Slides

FAIR data - Module 1 (research data) https://tess.elixir-europe.org/materials/fair-data-module-1 Research data and their centrality in the research process. This material is mostly in French. Gautier Sarah Hélène Chiapello Jean-François Dufayard Julien Seiler Lionel Maurel Paulette Lieby Thomas Denecker Biology Bioinformatics FAIR data Open science metadata, Data Life Cycle, Reproducibility, Data management plan Biologists bioinformaticians Biomedical researchers
IFB Shiny training

Shiny package training (in french)

Keywords: R-programming, Reproducible Science

IFB Shiny training https://tess.elixir-europe.org/materials/ifb-shiny-training Shiny package training (in french) Hélène Chiapello Jacques van Helden R-programming, Reproducible Science bioinformaticians statisticians
FAIR principles applied to bioinformatics

Content of the training material: - Introduction to reproducibility - encapsulate a work environment (docker) - design and execute workflows (snakemake) - IFB infrastructure (Slurm cluster) - managing software versions (git) - managing software environments (conda) - ensure...

Keywords: FAIR, Reproducible Science, Open science, Data analysis, Data processing

Resource type: Training materials

FAIR principles applied to bioinformatics https://tess.elixir-europe.org/materials/fair-principles-applied-to-bioinformatics Content of the training material: - Introduction to reproducibility - encapsulate a work environment (docker) - design and execute workflows (snakemake) - IFB infrastructure (Slurm cluster) - managing software versions (git) - managing software environments (conda) - ensure the traceability of analysis using Notebooks. The training material is in french Hélène Chiapello FAIR, Reproducible Science, Open science, Data analysis, Data processing bioinformaticians software developers, bioinformaticians computational scientists Researchers