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#Repositories #Data Publishing #Genotyping Data #MIAPPE #Plant Phenotyping Data #FAIR Principles

FAIR Cookbook - Plant genomic and genetic variation data submission to EMBL-EBI databases

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Description

The 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.

Details

URL: https://faircookbook.elixir-europe.org/content/recipes/reusability/miappe.htmlCommunities:

Target Groups:

Data Steward
Researcher

Proficiency Levels:

Competent

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

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Languages

English

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Text

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Keywords

Webinar on Plant Data Management for Phenotyping ExperimentsThe Minimal Information About Plant Phenotyping Experiment, MIAPPE (www.miappe.org) has been designed by ELIXIR, EMPHASIS and Bioversity international to guide plant scientists in the management of experimental data and to facilitate integration with genotyping data.The webinar gives an overview of the current practices and methods for plant phenotyping data standardization.

Learning Resource Type

Lecture

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PDF

Languages

English

Media Type

Presentation

Publication Date

2021-04-02

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Size

3.1 MB

Authors

Cyril Pommier

#MIAPPE #Data Management #BrAPI #Ontologies #Phenotyping Experiments #Plant Data

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Learning Resource Type

Lecture

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Unknown

Languages

English

Media Type

Video

Publication Date

2021-04-02

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Authors

Cyril Pommier

#MIAPPE #Data Management #BrAPI #Ontologies #Phenotyping Experiments #Plant Data

Keywords

Combining the BIDS and ARC Directory Structures for Multimodal Research Data OrganizationInterdisciplinary collaboration and integration of large and diverse datasets are becoming increasingly important. Answering complex research questions requires combining and analysing multimodal datasets. Research data management follows the FAIR principles making data findable, accessible, interoperable, and reusable. However, there are challenges in capturing the entire research cycle and contextualizing data according, not only for the DataPLANT and NFDI4BIOIMAGE communities. To address these challenges, DataPLANT developed a data structure called Annotated Research Context (ARC). The Brain Imaging Data Structure (BIDS) originated from the neuroimaging community extended for microscopic image data. Both concepts provide standardised and file system based data storage structures for organising and sharing research data accompanied with metadata. We exemplarily compare the ARC and BIDS designs and propose structural and metadata mapping.

Learning Resource Type

Poster

File Format

PDF

Languages

English

Media Type

Image

Publication Date

2023-09-12

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Size

2.9 MB

Authors

RDMkit - Plant ScienceThe RDMkit is a guide for 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. This section describes domain-specific aspects as well as Tools and Resources for plant science. It focuses on the planning of plant science data management, as well as the collection of phenotyping data and genotyping data.

Learning Resource Type

Cookbook

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Unknown

Languages

English

Media Type

Text

Publication Date

2023-12-20

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Authors

Erwan Le Floch

| Sebastian Beier

| Daniel Faria

| Erwan Le Floch

| Sebastian Beier

| Daniel Faria

#Plant Phenotyping Data #Data Collection #Data Management Planning #Plant Genotyping Data

Keywords

Plant genomic and genetic variation data submission to EMBL-EBI databasesThis 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 (https://fairsharing.org/bsg-s000543/). 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 (See details in Section 4.2).

Learning Resource Type

Web page

File Format

HTML

Languages

English

Media Type

Text

License

Keywords

#botany