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The Research Data Management toolkit for Life Sciences: Plant Sciences
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The Research Data Management toolkit for Life Sciences: Plant SciencesData management for Plant Sciences.
Learning Resource Type
Web page
File Format
HTML
Languages
English
Media Type
Text
License
CCBY
Authors
Keywords
#botany
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The Research Data Management toolkit for Life Sciences: Best practices and guidelines to help you make your data FAIR (Findable, Accessible, Interoperable and Reusable)
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The Research Data Management toolkit for Life Sciences: Best practices and guidelines to help you make your data FAIR (Findable, Accessible, Interoperable and Reusable)The ELIXIR Research Data Management Kit (RDMkit) has been designed to guide life scientists in their efforts to better manage their research data following the FAIR Principles. It is based on the various steps of the data lifecycle, although not all the steps will be relevant to everyone. RDMkit is recommended in the Horizon Europe Program Guide (https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021-2027/horizon/guidance/programme-guide_horizon_en.pdf) as the "resource for Data Management guidelines and good practices for the Life Sciences."
Learning Resource Type
Web page
File Format
HTML
Languages
English
Media Type
Text
License
CCBY
Authors
Keywords
#life sciences
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FAIR Cookbook - Plant genomic and genetic variation data submission to EMBL-EBI databases
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FAIR Cookbook - Plant genomic and genetic variation data submission to EMBL-EBI databasesThe FAIR Cookbook is an online, open and live resource for the Life Sciences with recipes that help you to make and keep data Findable, Accessible, Interoperable and Reusable; in one word FAIR. This recipe provides guidance for submitting plant genotyping data to public repositories. It explains in a step-wise fashion which work should be done and when. Special attention should be paid to the metadata maintenance of the data that will be deposited in different repositories as part of this recipe. A prerequisite for fully understanding this recipe is a basic knowledge of the MIAPPE standard. The exact listing of the metadata fields required for a FAIRification of the genotyping data set within a VCF file is also part of this recipe with examples and explanations.
Learning Resource Type
Cookbook
File Format
MD
Languages
English
Media Type
Text
License
CCBY
Authors
Keywords
#FAIR#Repositories#BioSamples#Data Publishing#Genotyping Data#MIAPPE#Plant Phenotyping Data
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FAIR Cookbook - Publication of plant experimental data in generic data repositories
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FAIR Cookbook - Publication of plant experimental data in generic data repositoriesThe FAIR Cookbook is an online, open and live resource for the Life Sciences with recipes that help you to make and keep data Findable, Accessible, Interoperable and Reusable; in one word FAIR. This recipe describes best practices for submitting plant experimentation data to generic data repositories (e.g. e!DAL-PGP, Dataverses such as recherche.data.gouv, dmportal.biodata.pt and Jülich DATA). This will allow data reuse according to FAIR principles, and especially to ensure visibility and reuse of genetic and phenomic datasets via minimal and sufficient description: data type, organism, list of plant material used, experimental metadata including methods and protocols, etc. Maximizing data visibility by allowing their indexation in international portals, as well as ensuring the interoperability of data sets in relation to a coherent identification of plant material used in experiments of various kinds (phenotyping, genotyping, genomics, etc.).
Learning Resource Type
Cookbook
File Format
MD
Languages
English
Media Type
Text
License
CCBY
Authors
Keywords
#Repositories#Data Publishing#Genotyping Data#MIAPPE#Plant Phenotyping Data#FAIR Principles
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