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The main objective of this deliverable is to provide resources that can assist life sciences researchers and data stewards in creating reference Data Management Plans (DMPs) for their research projects. The resources provided in this deliverable are intended to promote good research data management practices across the EU research landscape. To achieve this objective, a range of activities were undertaken, with a particular focus on the needs of the different domains covered by the demonstrator use-cases. In order to create these resources, the RDMkit pages were extended to include domain-specific information, which can be used as a reference when developing DMPs for different research projects. These pages fall under the "Your Domain" category and provide specific information on the data management needs and considerations for each domain. They also highlight challenges that are specific to each domain, such as data types, species, or areas, and offer solutions and considerations to overcome these challenges. In this deliverable, the RDMkit page for the Toxicology data demonstrator use-case was completed and added to the existing RDMkit pages for the other demonstrator use-cases. Additionally, a new Tool Assembly was added to the RDMkit corresponding to the Plant Sciences demonstrator use-case, covering the entire life cycle of experimental plant phenotyping data. In addition, the general Knowledge Models (KMs) of the Data Stewardship Wizard (DSW) were adapted to address the specific DMP questions needed for each demonstrator use-case. The DSW is a collaborative tool that enables data stewards and researchers to efficiently create DMPs for their research projects and it is designed with a hierarchical KM that guides users through the creation of DMPs. Since the relevant information for DMPs can vary across different domains, these KMs can be modified to contain the information relevant for each demonstrator use-case. For this deliverable, special focus was put on two of the demonstrator use-cases, namely Toxicology and Epitranscriptomics data. Additionally, related to the Human Data use-case, separate efforts are underway to enhance the sensitive data section of the KM system to ensure the proper management of such data. The improvements and new question suggestions that were found during these sessions were incorporated into the DSW KM by the DSW team. Furthermore, DMP templates were created in DSW for the demonstrator use-case using two standard approaches: creating a KM or a project template (PT). When creating a PT, a set of answers is saved and can be used to generate a partially pre-filled questionnaire for a new project. In the ideal case scenario, the two methods can be used together to provide domain-specific recommendations by answering questions that better reflect a scientific domain, such as metadata standards. In conclusion, this deliverable provides several valuable resources for life sciences researchers and data stewards, including extended RDMkit pages, customised DSW KMs, domain-specific DMP templates, and a new KM for creating DPIAs. These resources are designed to encourage good research data management practices across the EU research landscape, ensuring that valuable research data is effectively managed before, during, and after a project.

The overall goal of ELIXIR-CONVERGE’s WP5 was, based on the analysis of a set of very diverse use cases, to contribute to the development of a set of resources supporting the development and implementation of Data Management Plans (DMPs) in national and transnational projects. Six use cases were considered to co-develop and test a method to address domain specific data management planning associated to a set of resources in collaboration with WP1, WP2 and WP3. In this context, another objective of WP5 was to develop, implement and refine key performance indicators (KPIs) in order to monitor the demonstrator projects’ implementation of data management plans and possibly assess their adoption by the relevant community. WP5 developed two sets KPIs in collaboration with WP4, in charge of developing KPIs across the entire ELIXIR-CONVERGE project and for assessing the impact of the project : a first set aiming at monitoring the development of guidance, resources for the development of DMP and for training in the context of the use cases a second set aiming at addressing the adoption of these resources by relevant communities of users as a way to assess the impact of the work achieved In parallel, in order to ensure long term maintenance/update of the developed resources and to increase their impact, WP5 started to engage with ELIXIR communities that could be natural owners of these resources. The KPI developed and collected by WP5 during the ELIXIR-CONVERGE project were useful to follow the partner’s progress in the development and test of a sort of starter kit for domain specific data management support. Success stories could be collected showing adoption by communities and new projects and were mapped on ELIXIR’s categories of impacts showing already “hits” on several of these.

One of the objectives of WP5 was to identify the needs in terms of capacity building, in the context of the 6 use cases, and to develop strategy(ies) in collaboration with WP2 to address these needs. This was achieved in three steps: Create an inventory of training resources available in the context of the use cases Send an online survey followed by a series of F2F meetings with each use case to collect their training needs Test the development of learning paths as a method to develop a structured overview of training needs in relation to a use case The method set up by the ELIXIR Training Platform to better structure the development of training resources was proved very helpful to specify the needs in terms of training and capacity building in the context of the use cases. Spelling out the priority in terms of training target and the learning path to follow to reach this target is a way to detail the different modules that are necessary. It is then possible to map on these modules the training resources that are already available and to derive a list of gaps. This method was applied for three demo cases successfully in the Plant, Marine metagenomics and Human Genome data contexts. In terms of general organisation of community resources to facilitate this type of approach, the most important actions are to make the training materials accessible for reuse and easy to find. Versioning is highly desirable, to facilitate collaborative development and maintenance of training material of the time and a DOI attribution will facilitate citation and long term findability. Findability requires additional work to organise the training events and training resources in categories and/or facilitate filtering in the context of catalogues of training resources such as TeSS or Glittr or of knowledge hubs such as the RDMkit. This is achieved in TeSS, through the annotation of the training material and linked training events with ontology terms from EDAM, as well as with custom keywords. &nbsp

The international grapevine community has been working for a decade on recommendations and best practices to facilitate data exchange and reuse. Its first activity consisted in the development of a nomenclature system for grapevine genes that would allow consistent gene naming. The second was to propose a strategy aiming at facilitation grapevine data findability and reuse through recommendation on metadata standards, identifiers associated to samples which use will in turn facilitate the development of a centralized search tool across a federation of databases. The aim of the network was to make a step forward towards the implementation of this strategy by working on the three complementary pillars of success: improvement of the standards, ontologies and of guidelines for FAIR data management necessary to the grapevine community dissemination and training on these guidelines development of a federation of databases holding grapevine data, sharing the same metadata standards and identifiers, being all searchable through the same central portal and allowing data access and reuse. The first objective of this document is to set up the scene of the third pillar described above by: identifying the databases/information systems frequently used by the grapevine community checking how data (including metadata) can be accessed from these information systems Identifying possible problems and gaps The second objective is to make recommendations on steps to move forward towards the building of a federation of databases that would collaborate to provide central data services to the grapevine research community., This deliverable was developed upon work from COST Action CA 17111 INTEGRAPE, supported by COST (European Cooperation in Science and Technology).

Efficient sharing of plant phenotyping data is a challenge that has been addressed during the last two decades by European infrastructures (ELIXIR, EMPHASIS) and international communities (CGIAR), that allowed to coordinate the effort of major institutes developing activities in the domain. They produced consistent and interoperable sets of resources to support plant phenotyping data management: - data standards: Minimum Information About Plant Phenotyping Experiment (MIAPPE) and the Breeding API (BrAPI) - databases: PIPPA, PHIS, GnpIS, e!DAL-PGP among others - exchange file formats: MIAPPE Template, ISA-Tab These systems and standards have been designed to be as close as possible to researchers and experimenters needs. As a consequence, important efforts have been made to ease their adoption through documentations and trainings. However all these resources remain dispersed, and it can be complicated for new users to know where to get the right information. To address this issue, ELIXIR has developed in the frame of the ELIXIR-CONVERGE project a central portal of guidelines and resources supporting FAIR data management in Life Sciences: the Research Data Management toolkit (RDMkit). RDMkit is a one stop portal that gives a general overview and understanding of the complementarity of the solutions, and links back to the extended documentation and training materials maintained for each of them. To develop and sustain this portal, ELIXIR has engaged with various communities, infrastructures and projects, among which the ELIXIR plant science community and the AGENT project. In the RDMkit, the plant community has built a set of pages and in particular is building plant phenotyping guidelines. The present poster gives an overview of the RDMkit logic and of the solutions presented in the plant sciences pages, including the procedures and contact to submit enrichment and additional solutions.

Threats to global biodiversity are increasingly recognised by scientists and the public as a critical challenge. Molecular sequencing technologies offer means to catalogue, explore, and monitor the richness and biogeography of life on Earth. However, exploiting their full potential requires tools that connect biodiversity infrastructures and resources. As a research infrastructure developing services and technical solutions that help integrate and coordinate life science resources across Europe, ELIXIR is a key player. To identify opportunities, highlight priorities, and aid strategic thinking, here we survey approaches by which molecular technologies help inform understanding of biodiversity. We detail example use cases to highlight how DNA sequencing is: resolving taxonomic issues; Increasing knowledge of marine biodiversity; helping understand how agriculture and biodiversity are critically linked; and playing an essential role in ecological studies. Together with examples of national biodiversity programmes, the use cases show where progress is being made but also highlight common challenges and opportunities for future enhancement of underlying technologies and services that connect molecular and wider biodiversity domains. Based on emerging themes, we propose key recommendations to guide future funding for biodiversity research: biodiversity and bioinformatic infrastructures need to collaborate closely and strategically; taxonomic efforts need to be aligned and harmonised across domains; metadata needs to be standardised and common data management approaches widely adopted; current approaches need to be scaled up dramatically to address the anticipated explosion of molecular data; bioinformatics support for biodiversity research needs to be enabled and sustained; training for end users of biodiversity research infrastructures needs to be prioritised; and community initiatives need to be proactive and focused on enabling solutions. For sequencing data to deliver their full potential they must be connected to knowledge: together, molecular sequence data collection initiatives and biodiversity research infrastructures can advance global efforts to prevent further decline of Earth's biodiversity.

The deliverable D19/D4.4 of the GenRes Bridge project presents the overarching strategy on the documentation on Genetic Resource that has been developed to complement the overarching European Strategy on Genetic Resources (D2.4) and the new specific strategies of the three European networks of conservation of genetic resources, ECPGR, ERFP and EUFORGEN. A brief overview of the current global context concerning data on biodiversity, the achievements and current gaps of the three networks’s documentation activities is provided. This is completed by an overview of some important aspects of the legal frame of constraints and opportunities arising from the current ecosystem of initiatives supporting open science. The strategy proposes to leverage and adapt to the field of documentation on genetic resources the resources developed by the scientific community to support good data management practices compliant to the FAIR principles and ensure the development of a Findable, Accessible, Interoperable and Reusable wealth of data on genetic resources. The first set of proposed activities that should be developed at an overarching level by the networks where relevant are: development of standards, technology watch, training, capacity building and awareness raising on the importance of adopting and supporting good data management practices. Ultimately, they aim at increasing the quantity and the quality of data in the central repositories of the networks and at getting these repositories internationally recognized as trusted and FAIR compliant repositories. Another set of activities will allow the three networks to increase their participation in international initiatives developing the guidelines and resources supporting open linked data in relation with research and innovation in the areas of biodiversity, agriculture and forestry.

The goal of ELIXIR Converge WP5 is to assess the capacity of ELIXIR and its national nodes to assist users’ projects in implementing Data Management Plans (DMPs) in their projects at a EU scale. To do that, six demonstrator use-cases were created and they are described in the previous deliverable (D5.1). This deliverable includes a description of the main resources that can be used to assess researchers in the process of creating DMPs for at least two use-cases including a gap analysis. The DMPs are related to the demonstrator use-case #1 (Plant sciences) and #3 (Marine metagenomics). Moreover, specific aspects for use-cases #4 (Human data) and #6 (Biomolecular simulation) are also added. The main activities described in this deliverable are related to the ELIXIR Research Data Management Kit (RDMkit) and the Data Stewardship Wizard (DSW) in connection with ELIXIR Converge WP3 activities. For all use-cases except use-case 5 (Toxicology data), a ‘Your domain’ page in the RDMkit has been assembled with the information necessary to consider when managing research data in their corresponding domains. Also, a ‘Tool assembly’ page in the RDMkit for the plant sciences, marine metagenomics and human data use-cases have been added. Finally, the DSW has been used to perform the initial description of the first DMPs including a gap analysis. Since ELIXIR Converge started, the work of WP5 has been centered in understanding the needs of the demonstrator use-cases to develop, if necessary, customized DMPs for each of them considering the domains they are part of. Also, once this characterization was done, several resources have been created to help users in the development of their DMPs. Indeed, these demonstrators are expected to serve as examples for researchers developing their own DMPs. The domain and tool assemblies pages added in the RDMkit are ready to use internally in ELIXIR after the beta-release in February, 2021. They provide a valuable resource for researchers and data stewards in the life sciences to help them in their data management processes. The Knowledge Models (KMs), the central component of the DSW, are under periodic revision to incorporate outcomes from ELIXIR Converge including specific aspects identified by the use-cases in order to complete their content and release an official version of them. The final objective is to provide refined DMP versions for the remaining 4 use-cases. This will allow us to cover a broad range of data-driven demonstrators, with its associated challenges, and assess how the general process scales up when applied to other communities served by ELIXIR. All these efforts will contribute to harden the work developed in other ELIXIR Converge WPs like the RDMkit and the DSW (WP3), the dedicated training materials and capacity building actions (WP2) as well as to provide reference information to the data management experts network (WP1) and external members to the project, e.g. Industry, in WP4.

International audience

Task 5.1 aims to analyse the different demonstrators in light of the process necessary to implement their DMPs and to propose a categorisation based on users’ needs. This effort will provide input to WP1 with respect to needs in terms of experts and resources across ELIXIR Nodes (Task 1.3, Business plans). It is expected that some of them will be generic whereas others will be very specific to projects, which is an important factor for establishing a strategy towards the sustainability of such a service in all its diversity. D5.1 therefore describes the needs in terms of DMP of the demonstrator use-cases and proposes a project categorisation from the point of view of: - Area of expertise - The resources they use / toolkit - Training needs The first challenge was to develop a method to describe the needs of the users and their current practices in terms of data management as a prerequisite to the development of an adequate toolkit. The method adopted with the guidance of WP2 and WP3 relied on the description of users stories, and scenarios for different types of personas. In addition, a table was also developed to collect knowledge on the current practices and existing resources in terms of data management with guidance from WP1 and WP3. The six demonstrator use-cases are divided into two waves to facilitate having a broad diversity of data types, potential users and variable expertise and, at the same time, have first mature demonstrator use-cases that can start providing input to other WPs in the projects. The Plant and the Marine Metagenomics demonstrator use-cases were used as testers for the method developed as they are the two selected ones for the first wave. Federated access to human genomics data belongs to the second wave of demonstrator use-cases. However, considering its broad reach, it has been partially developed for this deliverable. User stories and scenarios with personas were developed by WP5 partners on the Plant, Marine metagenomics and Federated access to human genomics data: GDPR use-cases. The table on existing tools and resources was also filled in by WP5 partners and target interviews of researchers for some of the demonstrator use-cases. Additional input was sought from the ELIXIR communities for the demonstrator use-cases mentioned before. This method implemented to describe the demonstrator use-cases in detail has been efficient to isolate the specific context of each case, and to identify specific tools/resources in relation with the use-cases that can be used for data management. The main aspect used to classify a new use-case is the type of biological material linked to the data that links to many specific requirements, e.g. legal and scientific metadata. The second is the relation of the personas with the data, e.g. consumers/producers, and the type of data, including workflows, models, and the various types of experimental data. The landscape analysis of the resources already available in relation with the demonstrator use-cases and the different stages of a data management plan, showed that the guidelines developed by WP1 are very useful to clarify the scope of these stages before filling such a survey. The personas/users related to the use-cases are very diverse but always include the researchers in various positions, e.g. data consumer, data producer, data owner, PI writing a proposal, and the data curators. This will be further developed in collaboration with WP2. Finally, the work achieved to deliver D5.1 facilitated the development of pages dedicated to the “domains” in the RDMKit website (https://rdmkit.elixir-europe.org/) for demonstrator use-case 1, 3, 4 and 6. In these pages, specific challenges linked with the demonstrator use-cases are highlighted, and dedicated resources to solve them are listed. These tools have also been flagged in bio.tools with the domain name.

Task 5.1 aims to analyse the different demonstrators in light of the process necessary to implement their DMPs and to propose a categorization based on users’ needs. This effort will provide input to WP1 with respect to needs in terms of experts and resources across ELIXIR Nodes (Task 1.3, Business plans). It is expected that some of them will be generic whereas others will be very specific to projects, which is an important factor for establishing a strategy towards the sustainability of such a service in all its diversity.D5.1 therefore describes the needs in terms of DMP of the demonstrator use-cases and proposes a project categorization from the point of view of :- Area of expertise- The resources they use / toolkit- Training needsThe first challenge was to develop a method to describe the needs of the users and their current practices in terms of data management as a prerequisite to the development of an adequate toolkit. The method adopted with the guidance of WP2 and WP3 relied on the description of users stories, and scenarios for different types of personas. In addition, a table was also developed to collect knowledge on the current practices and existing resources in terms of data management with guidance from WP1 and WP3. The six demonstrator use-cases are divided into two waves to facilitate having a broad diversity of data types, potential users and variable expertise and, at the same time, have first mature demonstrator use-cases that can start providing input to other WPs in the projects. The Plant and the Marine Metagenomics demonstrator use-cases were used as testers for the method developed as they are the two selected ones for the first wave. Federated access to human genomics data belongs to the second wave of demonstrator use-cases. However, considering its broad reach, it has been partially developed for this deliverable. User stories and scenarios with personas were developed by WP5 partners on the Plant, Marine metagenomics and Federated access to human genomics data: GDPR use-cases. The table on existing tools and resources was also filled in by WP5 partners and target interviews of researchers for some of the demonstrator use-cases. Additional input was sought from the ELIXIR communities for the demonstrator use-cases mentioned before.This method implemented to describe the demonstrator use-cases in detail has beenefficient to isolate the specific context of each case, and to identify specific tools/resources in relation with the use-cases that can be used for data management.The main aspect used to classify a new use-case is the type of biological material linked to the data that links to many specific requirements, e.g. legal and scientific metadata. The second is the relation of the personas with the data, e.g. consumers/producers, and the type of data, including workflows, models, and the various types of experimental data. The landscape analysis of the resources already available in relation with the demonstrator use-cases and the different stages of a data management plan, showed that the guidelines developed by WP1 are very useful to clarify the scope of these stages before filling such a survey.The personas/users related to the use-cases are very diverse but always include the researchers in various positions, e.g. data consumer, data producer, data owner, PI writing a proposal, and the data curators. This will be further developed in collaboration with WP2. Finally, the work achieved to deliver D5.1 facilitated the development of pages dedicated to the “domains” in the RDMKit website (https://rdmkit.elixir-europe.org/) for demonstrator use-case 1, 3, 4 and 6. In these pages, specific challenges linked with the demonstrator use-cases are highlighted, and dedicated resources to solve them are listed. These tools have also been flagged in bio.tools with the domain name.

Annex 1 to ELIXIR-CONVERGE Deliverable D5.1 - Categorisation of the pilot projects

The 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. A recording of the webinar is available:https://youtu.be/Fq2j16jzdBA The webinar was organized in the frame of the AGENT and GenRes Bridge projects that received funding from the European Union’s Horizon 2020 research and innovation programme under respective grant agreements No 862613, and No 817580.

International audience; INRA is involved in several EU infrastructures (e.g. ELIXIR, EMPHASIS) or global initiatives (e.g. Wheat Initiative, Research Data Alliance) contributing to the development of : (i) community recommendations for data standardization (e.g. Dzale-Yeumo et al 2017, https://doi.org/10.12688/f1000research.12234.2), (ii) data standards for phenotyping data (www.miappe.org), (iii) crop specific ontologies in the frame of the CropOntology (http://www.cropontology.org/) and (iv) standard web services (www.brapi.org). These global resources are used to capture the data produced in large scientific projects with a standard and structured vocabulary and to store them into INRA’s central repository for plant genomic, phenomic and genetic data, GnpIS (https://urgi.versailles.inra.fr/gnpis/) under the FAIR principles (https://www.force11.org/group/fairgroup/fairprinciples). In parallel, we have developed tools to support federation of databases. The first one is a light data discovery tool based on text indexing technologies, which allows to find data across several distinct databases based on a common high level generic data model (Spannagl et al 2016). The current federates 15 databases from 6 countries (https://urgi.versailles.inra.fr/wheatis/). Another tool allowing data search on phenotyping data and based on BrAPI web services is also about to be released in the frame of the H2020 ELIXIR-Excelerate project, n°676559. The long term resilience and success of such federations will highly depend on the capacity to animate and structure the community working on data for plant biology.

International audience

High-throughput “omics” technologies are widely used and increasingly important to support plant biology research and breeding of diverse plant species for production of food, feed, fibre and other biomaterials, and bio-energy. Significant advances in plant science can be obtained from the integration of available genomic and genotyping data with diverse types of phenotyping data, including field or greenhouse experimental data, molecular, -omics and image data. Although most -omics data, and especially phenomic data, are being generated in increasing scale, either from public or private research institutes, the dispersion of datasets and metadata among multiple repositories and their often poor description and annotation, make their use and exploitation still challenging or even unapproachable. To help unlock the full potential of a multi-omics approach to plant science, the overarching goal of this work package is to make plant data reusable and interoperable in accordance with the FAIR principles (i.e. Findable, Accessible, Interoperable and Re-usable). Hence, several standards have been built these past years for the annotation of data sets, and the ELIXIR plant community is co-authoring most of them. Their use has been demonstrated by exemplary application to data from diverse species published in public repositories (Deliverable 7.1). They are also the foundation of the ELIXIR Plant Data Search Service, FAIDARE, that gives access to distributed and standardized datasets. This service uses the Breeding API (BrAPI1), an API for accessing data relevant for plant breeding developed by the international plant community (Deliverable 7.2). It is based on a federation of plant phenotyping/genotyping data repositories, accessible through a single data discovery webportal2, that connects not only ELIXIR data repositories, but also any other Breeding API compatible database. This work represents a major step towards plant FAIR data and a significant tool for the international plant community focused on plant breeding, either of crops or forest trees. Furthermore, with this deliverable we reach the main goal of WP7, to provide a distributed infrastructure to allow plant genotype-phenotype analysis based on the widest available public datasets, and we give an important contribution to address goal one of the ELIXIR-EXCELERATE project: Deliver world-leading data services for academia and industry.

International audience

Plant omics data is often not published, or dispersed among multiple repositories and,owing to poor annotation of submissions with descriptive metadata, effectively not FAIR(i.e. Findable, Accessible, Interoperable and Re-usable). In this work package, our goal isto make plant -omics data FAIR, and the first part of this work has involved thedevelopment of standards for the annotation of data sets, and their exemplary applicationto diverse data from diverse species. Finally, the annotated data has been made availablein the public repositories. In developing these standards, we have built from previous work in the field, most notablythe development of the Minimal Information about a Plant Phenotyping experiment(MIAPPE) standard (http://www.miappe.org). We have taken MIAPPE as our startingpoint, and extended and revised it according to the characteristics of our exemplar data. Because a proposed standard becomes a real one through its adoption, we have activelyparticipated in the wider community developing MIAPPE, with the goal of incorporatingour developments within the official MIAPPE specification. A particularly important issue is the identification of material used in an experiment.Materials used within and between experiments may be related to each other (by time,space, condition or genealogy), and multiple assays may be taken from the samematerial; moreover, what is often of interest is to connect experimental data to thephysical material assayed (or at least, related physical material, such as a stock held in agermplasm repository). We have taken special care in aligning the MIAPPE standardswith the FAO Multi Crop Passport Descriptor Data standard used by the gene banks andused the BioSamples database (http://www.ebi.ac.uk/biosamples) as an integrative layerto allow us to capture the relationships between samples and the measurements thathave been made upon them.

Grapevine is a very important crop species that is mainly cultivated worldwide for fruits, wine and juice. Identification of the genetic bases of performance traits through association mapping studies requires a precise knowledge of the available diversity and how this diversity is structured and varies across the whole genome. An 18k SNP genotyping array was evaluated on a panel of Vitis vinifera cultivars and we obtained a data set with no missing values for a total of 10207 SNPs and 783 different genotypes. The average inter-SNP spacing was ~47 kbp, the mean minor allele frequency (MAF) was 0.23 and the genetic diversity in the sample was high (He = 0.32). Fourteen SNPs, chosen from those with the highest MAF values, were sufficient to identify each genotype in the sample. Parentage analysis revealed 118 full parentages and 490 parent-offspring duos, thus confirming the close pedigree relationships within the cultivated grapevine. Structure analyses also confirmed the main divisions due to an eastern-western gradient and human usage (table vs. wine). Using a multivariate approach, we refined the structure and identified a total of eight clusters. Both the genetic diversity (He, 0.26–0.32) and linkage disequilibrium (LD, 28.8–58.2 kbp) varied between clusters. Despite the short span LD, we also identified some non-recombining haplotype blocks that may complicate association mapping. Finally, we performed a genomewide association study that confirmed previous works and also identified new regions for important performance traits such as acidity. Taken together, all the results contribute to a better knowledge of the genetics of the cultivated grapevine, The GrapeReSeq project (Large scale resequencing in the Vitis genus for identification of resistance genes, SNP discovery and high throughput genotyping) was funded by Research project of Transnational Plant Alliance for Novel Technologies toward implementing the Knowledge Based Bio-Economy (PLANT - KBBE2008) in Europe (France, Germany and Spain)

International audience; Plant Phenotyping data management following the FAIR (Findable, Accessible, Interoperable, Resusable) is highly challenging because of its heterogenity. Thus, simply integrating and consolidating data within a single dataset like a phenotyping network is already a complicated task which is even more complex when trying to link different datasets together. To adress this problem, the Minimal Information About Plant Phenotyping Experiment standard construction has been initiated four years ago, with the help of experts from European infrastructures and institutes like Elixir, Emphasis, INRA, WUR, iBet, IPK, EBI and IPG PAS. It adresses the need of data publication and reuse through a checklist that formalize and document the minimal metadata necessary to ensure long term FAIRness of field or greenhouse datasets, including high througputs phenotyping ones. This list has been implemented in several databases like GnpIS or eDale, in a file format, ISA Tab, in a web service, the Breeding API and an RDF implementation is under construction. We will review those implementations, show its current adoption state and detail the plans for the future evolutions of the standard.

Plant Phenotyping data management following the FAIR (Findable, Accessible, Interoperable, Resusable) is highly challenging because of its heterogenity. Thus, simply integrating and consolidating data within a single dataset like a phenotyping network is already a complicated task which is even more complex when trying to link different datasets together. To adress this problem, the Minimal Information About Plant Phenotyping Experiment standard construction has been initiated four years ago, with the help of experts from European infrastructures and institutes like Elixir, Emphasis, INRA, WUR, iBet, IPK, EBI and IPG PAS. It adresses the need of data publication and reuse through a checklist that formalize and document the minimal metadata necessary to ensure long term FAIRness of field or greenhouse datasets, including high througputs phenotyping ones. This list has been implemented in several databases like GnpIS or eDale, in a file format, ISA Tab, in a web service, the Breeding API and an RDF implementation is under construction. We will review those implementations, show its current adoption state and detail the plans for the future evolutions of the standard.