# Rendre ses données "FAIR" - Contexte et Infrastructures

Anne-Francoise Adam-Blondon

► To cite this version:

Anne-Francoise Adam-Blondon. Rendre ses données "FAIR" - Contexte et Infrastructures. Colloque Etude du Polymorphisme des Génomes Végétaux (EPGV), Oct 2018, Evry, France. pp.28. hal-02786578

HAL Id: hal-02786578

https://hal.inrae.fr/hal-02786578v1

Submitted on 5 Jun 2020

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Distributed under a Creative Commons CC BY 4.0 - Attribution - International License
# Rendre ses données « FAIR »-contexte et infrastructures

Anne-Françoise Adam-Blondon

Colloque EPGV, 4 octobre 2018

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Contexte actuel des sciences de la vie

Open science ... open access, open data

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*"The days of keeping our research results to ourselves are over. There is far more to gain from sharing data and letting others access and analyse that data.*

For example, if sharing big data reveals that a certain kind of cancer activates a particular molecular pathway in most cases and it turns out that there is already a drug approved and available to block the activation of that molecular pathway, clinical trials can begin almost immediately. Saving time, money and lives.

Or if scientists want to monitor the effects of climate change on local ecosystems, they can use Open Science to engage citizen reporting, and rapidly multiply the data at their disposal.

To make the most of Open Science opportunities for Europe, I plan to focus on open data, open access and research integrity over the course of my mandate.*

*Commissioner Carlos Moedas,*

*"European research and innovation for global challenges", Lund, 4 December 2015*
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Les données sont dispersées
dans un "écosystème" de
systèmes d'information
Les données sont dispersées dans de nombreux systèmes d'information

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=> Aller vers des fédérations de systèmes d'information
interopérables qui permettent aux chercheurs de les trouver
# Organisation de ces fédérations

* Un réseau de nœuds (stables)

* Un portail central offrant des services (a minima: trouver et accéder aux données)

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# Enjeux clefs des E-infrastructures

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Recommandations développées par un collectif de bibliothécaires, établissement d'enseignement et de recherche pour l'Open Data en sciences

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Wilkinson et al (2016) SCIENTIFIC DATA, 3:160018, DOI: 10.1038/sdata.2016.18
# Organisation des e-Infrastructures européennes

* European Open Science Cloud (EOSC)

* European Infrastructure of Bioinformatics for Life-sciences: ELIXIR

ELIXIR mission and strategy aligns with EOSC - implement life-science foundation in EOSC-Life

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FAIR data management in the
life sciences

10.7490/f1000research.1114985.1

Gateway for User access and
mechanism for exposing
life-science services (via ELIXIR
Registries)

Compatible Cloud /
Workflows / Reference Data
Set Distribution Service
# ELIXIR, a distributed pan-European infrastructure

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## ELIXIR: The French Node

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The French bioinformatics community is currently setting up a national infrastructure of services in Bioinformatics (Institut Français de Bioinformatique, IFB). IFB serves as a unique entry point for requests of service from the Life Science community and is in charge of

coordinating and structuring the activities of the regional bioinformatics platforms. IFB is the French ELIXIR node

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Inserm

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CEA

### Collaborating organisations

IFB consists of a national hub, IFB-core, and more than 20 bioinformatics platforms organized in six regional centres. These PFS belong to the main French research organisations:

* CNRS: National Centre for Scientific Research

* CEA: Alternative Energies and Atomic Energy Commission

* InRA: National Institute for Agriculture Research

* InITA: National Institute for Computer Science and Control

* INSERTM: National Institute for Health and Medical Research

* Universities

* Pasteur Institute (research foundation)

* Curie Institute (research foundation)

IFB comprises more than 110 FTE and 70 FTC researchers and engineers.

This represents 25% of the French Bioinformatics community that is involved in provision of service for the Life Sciences.

### Services

To provide added value to various data produced remotely by biological platforms and newly created national infrastructures in sequencing, genotyping, proteomics, metabolomics, etc., the French node will focus on the development of services for integrative curation of biological data.

Keywords of IFB contributions are thus Interoperability (technological and semantic) and integratation.

IFB will provide access to well-curated databases, tools and services in:

* these biological domains:

* D-1: Microbial world

* D-2: Plants

* D-3: Health

* two transmembrane fields:

* A-1: Physiology and classification

* A-2: Protein sequence and structures

* and two transmembrane activities:

* T-1: Management and analysis of metagenomic data

* T-2: Deployment of an academic cloud dedicated to analyses of Life Science data

Building on the training and education programs already proposed by the regional PFS, IFB will endeavour to coordinate and compile a national training and education program based on e-learning technologies.

<figure><img src="image_20.png" /><figcaption>Integrative Curation</figcaption></figure>

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## Contact

Dr. Jean-François Elizir
Head of IFB
Unit of Research
CNRS/Inserm
An Avenue des Monts
65452 Cedex 9

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ifb

ANR

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* 23 pays impliqués

* Le Nœud Français est porté par l'IFB
# Objectifs d'ELIXIR

In 2023: Continent-scale, standards-based infrastructure for accessing and analysing life-science data

Marine metagenomics

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Human data

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Plants

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Metabolomics

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Galaxy Rare diseases

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Proteomics

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...delivered in partnership with research communities

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Communauté Plante d'ELIXIR coordonnée par C. Pommier (URGI) et C. Miguel (IBET, PT)
# Objectifs d'ELIXIR

FAIR publication, sharing and reuse of data require global standards

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Beacons/Local EGA – Federated Genomics Discovery & Query services

Standards and services for federated plant phenotyping data

Global collaborations for standards infrastructure
Findable

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# Findable

F1. (meta-)data are assigned a **globally unique and eternally persistent identifier**.

F2. data are described with **rich metadata**.

F3. (meta-)data are **registered or indexed in a searchable resource**.

F4. metadata **specify** the data identifier.

## Producteurs de données:

* dépôt de données dans des archives avec des métadonnées riches

## Informaticiens/curateurs de données:

* développement de services/catalogues de PUID ou persistent Identifiers (ex: DOI pour les accessions, ORCID ID pour les personnes, ...)

* développement de portails qui indexent les métadonnées et d'outils de recherche associés

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Modèles de données et sémantique pour améliorer la performance des recherches
# Plusieurs preuves de concept de portail de fédérations « plantes »

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EnsemblPlants

EMBL-EBI

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HELMHOLTZ
GEMEINSCHAFT

PLANTS DB

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IPK

GATERSLEBEN

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IGR
pan

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TGAC

The Genome Analysis Centre™

GrainGenes

A Database for Triticeae and Avena

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Gramene

CIMMYT

International Maize and Wheat Improvement Centre
Ex: fédération internationale WheatIS

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ROTHAMSTED
RESEARCH

Finland

Sweden

Russia

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EnsemblPlants

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Eartham
Institute

EMBL-EBI

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GrainGenes

A Database for Triticaceae and Avena

radi

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Gramene

CerealsDB

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United
Kingdom

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Germany

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France

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HELMHOLTZ
GEMEINSCHAFT

PLANTS DB

USDA

NIFA

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Triticean CAP

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UCW

United States

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Mexico

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Algeria

Mali

Niger

Sudan

Chad

Nigeria

Ethiopia

DR Congo

Kenya

Tanzania

Angola

Namibia

Botswana

Madagascar

South Africa

Turkey

Libya

Saudi Arabia

Iraq

Iran

Afghanistan

Pakistan

India

Thailand

China

Japan

South Korea

Venezuela

Colombia

Brazil

Peru

Bolivia

Chile

Argentina

Indo

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THE UNIVERSITY OF
WESTERN AUSTRALIA

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Australia

New
Zealand
Basé sur un modèle de données très gros grain

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Un portail: wheatis.org

WheatIS

Search

About

WheatIS nodes:

transPlant-MIPS (UP):

- CrowsNest: 13324

transPlant-IPK (UP):

- CR-EST: 199220

- GEBIS: 52878

- MetaCrop: 355

transPlant-EBI (UP):

- Ensembl Plants: 21828

transPlant-IPGPAS (UP):

- PlantPhenoDB: 2

T3 (UP):

- Triticaceae Toolbox: 1711

CIMMYT (UP):

- CIMMYT Datapo: 918

- CIMMYT dataverse: 37

URGI (UP):

- GnplS: 1757714

- Wheat3Bmine: 271197

- GnplS JBrowse: 23278

WheatIS

Filters

Clear

Database

- TRITICEAE TOOLBOX (64)

- CR-EST (7)

- GNPIS (3)

- ENSEMBL PLANTS (1)

- GNPIS JBROWSE (1)

- PLANTPHENODB (1)

Type

- ACCESSION (42)

- PHENOTYPE (14)

- EXPERIMENT (9)

- EXPRESSED SEQUENCE TAGS (7)

- SEQUENCE FEATURE (2)

- PHENOTYPE (1)

- QTL (1)

- SEQUENCE FEATURE (1)

Species

- TRITICUM AESTIVUM (69)

- HORDEUM VULGARE (6)

- TRITICUM AESTIVUM L. (1)

- TRITICUM DURUM (1)

Search

About

WheatIS nodes:

transPlant-MIPS (UP):

- CrowsNest: 13324

transPlant-IPK (UP):

- CR-EST: 199220

- GEBIS: 52878

- MetaCrop: 355

fhb

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1-10 of 77

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10 results per page

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<table><thead><tr><th>ID</th><th>Source</th><th>Type</th><th>Taxon</th><th>Description</th></tr></thead><tbody><tr><td>Traes_5DL_E12C501B4</td><td>Ensembl Plants</td><td>-</td><td>Triticum aestivum</td><td>Sequence feature, Ensembl Plants, Traes_5DL_E12C501B4, Traes_5DL_E12C501B4, Multiple inositol polyphosphate phosphatase Phytia1 [Source:UniProtKB/TrEMBL_Acc:A0FHB0], Triticum aestivum, protein_coding, 5D</td></tr><tr><td>HDP14M22T</td><td>CR-EST</td><td>-</td><td>Hordeum vulgare</td><td>HDP14M22T, expressed sequence tags, CR-EST, Hordeum vulgare, gi|26248924|ref|NP_754964.1| Hypothetical protein yfhB [Escherichia coli CFT073] Hypothetical prote; gi|28951047|gb|AAO63447.1| At2g37930 [Arabidopsis thaliana]..</td></tr><tr><td>HDP20D01w</td><td>CR-EST</td><td>-</td><td>Hordeum vulgare</td><td>HDP20D01w, expressed sequence tags, CR-EST, Hordeum vulgare, gi|15604676|ref|NP_221194.1| SFHB PROTEIN HOMOLOG (sfhB) [Rickettsia prowazekii str. Madrid E] SFHB : gi|34906406|ref|NP_914550.1| P0710E05.16 [Oryza sativa] ..</td></tr><tr><td>HDP20D01T</td><td>CR-EST</td><td>-</td><td>Hordeum vulgare</td><td>HDP20D01T, expressed sequence tags, CR-EST, Hordeum vulgare, gi|15604676|ref|NP_221194.1| SFHB PROTEIN HOMOLOG (sfhB) [Rickettsia prowazekii str. Madrid E] SFHB : gi|34906406|ref|NP_914550.1| P0710E05.16 [Oryza sativa] ..</td></tr><tr><td>HDP21C08T</td><td>CR-EST</td><td>-</td><td>Hordeum vulgare</td><td>HDP21C08T, expressed sequence tags, CR-EST, Hordeum vulgare, gi|15604676|ref|NP_221194.1| SFHB PROTEIN HOMOLOG (sfhB) [Rickettsia prowazekii str. Madrid E] SFHB : gi|31979237|gb|AAP68831.1| bone morphogenetic protein 1[..]</td></tr><tr><td>HDP31N10w</td><td>CR-EST</td><td>-</td><td>Hordeum vulgare</td><td>HDP31N10w, expressed sequence tags, CR-EST, Hordeum vulgare, gi|15604676|ref|NP_221194.1| SFHB PROTEIN HOMOLOG (sfhB) [Rickettsia prowazekii str. Madrid E] SFHB : gi|34906406|ref|NP_914550.1| P0710E05.16 [Oryza sativa] ..</td></tr><tr><td>HDP35A10T</td><td>CR-EST</td><td>-</td><td>Hordeum vulgare</td><td>HDP35A10T, expressed sequence tags, CR-EST, Hordeum vulgare, gi|26248924|ref|NP_754964.1| Hypothetical protein yfhB [Escherichia coli CFT073] Hypothetical prote; gi|28951047|gb|AAO63447.1| At2g37930 [Arabidopsis thaliana]..</td></tr><tr><td>TS034C007w</td><td>CR-EST</td><td>-</td><td>Triticum aestivum</td><td>TS034C007w, expressed sequence tags, CR-EST, Triticum aestivum, Gi|15233419|ref|NP_192328.1| hypothetical protein [Arabidopsis thaliana] gi|7487460|pir|T01820 hypo; Gi|15604676|ref|NP_221194.1| SFHB PROTEIN HOMOLOG (sfhB) ..</td></tr><tr><td>HWW FHB</td><td>Triticaceae Toolbox</td><td>Experiment</td><td>Triticum aestivum</td><td>Experiment, Triticaceae Toolbox, HWW FHB, phenotype experiment, Includes trials FHB_2014_Lincoln, HWWFHB_2014_Brookings, HWWFHB_2014_Fargo, Triticum aestivum, phenotype</td></tr><tr><td>URSN_2012_BrookingsSD</td><td>Triticaceae Toolbox</td><td>Experiment</td><td>Triticum aestivum</td><td>Experiment, Triticaceae Toolbox, URSN_2012_BrookingsSD, phenotype trial, traits=Fusarium head blight incidence, Fusarium head blight severity, Fusarium head blight disease index, visually scabby kernels URSN, descript[..]</td></tr></tbody></table>

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# Accessible

A1 (meta-data are *retrievable* by their identifier using a standardized communications protocol.

A1.1 the *protocol* is open, free, and universally implementable.

A1.2 the *protocol* allows for an authentication and authorization procedure, where necessary.

A2 **metadata are accessible**, even when the data are no longer available.

* **Producteurs de données:** dépôt de données et métadonnées sous PUID/DOI dans des archives/bases de données accessibles par le web (stables dans le temps) + licence d'accès définie dans les DOI, base de données

* **Informaticiens:** développement de web services (= Application Programming Interface: API)
Ex: 16 ans d'expérimentations du réseau Céréales à Pailles

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Collaboration URGI - IST

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# Breeding API initiative

http://www.brapi.org/

* Bill & Melinda Gates Foundation

* CassavaBase

* T3

* IBP

* JHI

* Bioversity

* CIRAD

* INRA

* IRRI

* GOBII

* Wageningen WUR

* CIP

* DaRT

* Cornell

* iPlant

* ...

* Développement d'une **API (web service) standard** pour les données dans le champ de la génétique et amélioration des plantes

* Materiel génétique, expériences de phénotypage, de génotypage, ...

* Alignement de l'API BrAPI avec les standards pour les données RG (MCPD) et pour les expériences de phénotypage (MIAPPE)
# Federation of Plant Information systems

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accelerate

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## BrAPI-based improved plant portal

* Easier to maintain

* Easier to improve the central services
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# Interoperable

1. (meta-)data use a **formal**, accessible, shared, and broadly applicable **language** for knowledge representation.

2. (meta-)data use **vocabularies** that follow FAIR principles.

3. (meta-)data include **qualified references to other (meta-)data**.

## Animation de différentes communautés (et de leurs interactions)

* Développeurs

* Spécialistes des ontologies et standards

* Curateurs de données

* Producteurs de données

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Infrastructures (internationales)

Projets focalisés espèces, objets de recherche

## En clarifiant

* ce qui est de la responsabilité de chacun dans le processus

* les concepts pivots pour faire de l'interopérabilité

* les standards existants
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# Interopérabilité des données

Crop Ontology

Variable=trait + method + scale

Identification : MultiCrop

Passport Data

Standard

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Phenotype 1 = **measurement** on a **cultivar** in an environment-**GPS1-time1**

Phenotype 2 = **measurement** on a **cultivar** in an environment-**GPS2-time2**

Genotype = observed marker's alleles on a **cultivar**

Climate 1 = climatic data at **GPS1-time1**

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Inspire EU directive
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# Différents niveaux de standardisation possible

* *Check list* d'informations décrivant le comment, par qui et pourquoi du jeu de données : **standard de métadonnées**

* **Dictionnaires de vocabulaires contrôlés, ontologies, échelles standards**: Crop Ontology, Gene Ontology, BBCH scales...

* **Identifiant uniques (idéalement persistents)**: gene ID, accessions ID, Trait ID, pubmed ID, DOI,...

* **Formats de fichiers**: VCF, IsaTab, GnpIS excel submission format, ...

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Domaine foisonnant et complexe: nécessité de développer des guides, catalogues et formations ciblées sur les différentes communautés
About

Collaborators

Search

Data Standards

Submit Data

Tools

Links

WheatIS Nodes

WheatIS

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Wheat Data Interoperability Guidelines

Home

Guidelines

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Ontologies & Vocabularies

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Use cases

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Getting involved

About

follow

9 Dec

ti...

4 Dec

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9 Dec

Welcome

These recommendations have been prepared by members of the Wheat Data Interoperability Working Group (WG), one of the WGs of the Research Data Alliance and the only WG of the Agriculture Data Interoperability Interest Group. The group is coordinated by members of the Wheat Initiative, a global initiative that aims to reinforce synergies between bread and durum wheat national and international research programmes to increase food security, nutritional value and safety while taking into account societal demands for sustainable and resilient agricultural production systems.

GETTING INVOLVED

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WheatIS

RESEARCH DATA ALLIANCE

More specifically, the WG aims to:

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PROMOTE

the adoption of common
standards, vocabularies and
best practices for Wheat data
management

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FACILITATE

access, discovery and reuse
of wheat data

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FACILITATE

wheat data integration

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Guidelines

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Ontologies &
Vocabularies

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Use Cases
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Reusable

R1. meta(data) have a plurality of accurate and relevant attributes.

R1.1. (metaicie) are released with a clear and accessible data usage
license.

R1.2. (meta-)data are associated with their provenance.

R1.3. (meta-)data meet domain-relevant community

Producteurs de données:

* Contribution à la définition des standards de métadonnées cohérents avec le domaine

* Publication des jeux de données sous DOI permet de spécifier l'ensemble des contributeurs et leurs rôles et les droits et conditions de réutilisation des données

Informaticiens/ bibliothécaires:

* Développement d'outils d'aide à la publication des jeux de données
# Developpement d'un standard de métadonnées pour les données de phénotypage

* MIAPPE: Minimum Information About Phenotyping Experiment

* Developpé et maintenu par une communauté internationale: maintained by an international community interested in plant phenotyping: large community of breeders and biologists, European infrastructure for Plant Phenotyping (EPPN/EMPHASIS), European infrastructure of Bioinformatics (ELIXIR), Planteome, Excellence in Breeding Plateform...

* www.miappe.org

* Steering committee avec des représentants de Emphasis, Elixir, CGIARs
# Remerciements

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H. Quesneville
C. Pommier
M. Alaux

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E. Dzale-Yeumo
S. Aubin

## Financial supports

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ANR

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RESEARCH DATA ALLIANCE

## International infrastructures/ initiatives

transPLANT

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elixir

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EMPHASIS

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Analysis and Experimentation on Ecosystems

France

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openMINTEC
Open Mining Infrastructure for Text & Data

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WHEAT INITIATIVE

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BrAPI

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Biodiversity International

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Planteome

## National and international crop projects

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Betterave2020

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Breed

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wheat

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PeaMUST

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RapsodyN

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BFF
Biomass For the Future

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AgroBRC

Wheatbi

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GENTREE

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International
Wheat Genome
Sequencing
Consortium

Pas que les plantes cultivées!
Merci!
# Catalogue (FAIR et durable) de recommandations et standards

Find

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Recommendations

Standards and/or databases recommended by journal or funder data policies.

Discover

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Collections

Standards and/or databases grouped by domain, species or organization.

Learn

<figure><img src="image_123.png" /></figure>

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About standards, their use in databases and policies, and how we can help you.

## Graph Viewer: Collections > Wheat Data Interoperability Guidelines

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DATABASE

POLICY

COLLECTION

TERMINOLOGY ARTIFACT

MODEL FORMAT

REPORTING GUIDELINE

RECOMMENDS

COLLECTS

IMPLEMENTS

RELATED TO

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EMBL

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Australia

Bioinformatics Resource

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FORCE11
The Future of Research Communications and a Scholarship

F1000
FACULTY of 1000

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PLOS

nature publishing group

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EMBO press

FAIR sharing.org
standards, databases, policies