Making experimental data tables in the life sciences more FAIR: a pragmatic approach

Jacob, Daniel; David, Romain; Aubin, Sophie; Gibon, Yves

doi:10.1093/gigascience/giaa144

Cited by 12 publications

(12 citation statements)

References 9 publications

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“…The metabolic dataset and all metadata were deposited online using Dataverse INRAE (https://dx.doi.org/10.15454/UUBXIF) and following the Findable, Accessible, Interoperable, Reusable (FAIR) principles (Jacob et al ., 2020).…”

Section: Data Availabilitymentioning

confidence: 99%

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Predictive metabolomics of multiple Atacama plant species unveils a core set of generic metabolites for extreme climate resilience

et al. 2022

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Current crop yield of the best ideotypes is stagnating and threatened by climate change. In this scenario, understanding wild plant adaptations in extreme ecosystems offers an opportunity to learn about new mechanisms for resilience. Previous studies have shown species specificity for metabolites involved in plant adaptation to harsh environments.Here, we combined multispecies ecological metabolomics and machine learning-based generalized linear model predictions to link the metabolome to the plant environment in a set of 24 species belonging to 14 families growing along an altitudinal gradient in the Atacama Desert.Thirty-nine common compounds predicted the plant environment with 79% accuracy, thus establishing the plant metabolome as an excellent integrative predictor of environmental fluctuations. These metabolites were independent of the species and validated both statistically and biologically using an independent dataset from a different sampling year. Thereafter, using multiblock predictive regressions, metabolites were linked to climatic and edaphic stressors such as freezing temperature, water deficit and high solar irradiance.These findings indicate that plants from different evolutionary trajectories use a generic metabolic toolkit to face extreme environments. These core metabolites, also present in agronomic species, provide a unique metabolic goldmine for improving crop performances under abiotic pressure.

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Section: Data Availabilitymentioning

confidence: 99%

“…A fascinating perspective will be to research the genetic and molecular mechanisms that control the levels of these metabolic markers. and following the Findable, Accessible, Interoperable, Reusable (FAIR) principles (Jacob et al, 2020). Table S5 Markers in control plant.…”

Section: Involvement Of the Best Metabolic Predictors In Extreme Envi...mentioning

confidence: 99%

Predictive metabolomics of multiple Atacama plant species unveils a core set of generic metabolites for extreme climate resilience

et al. 2022

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“…[12]. Making data compliant with the FAIR principles is still at a trial phase regarding which criteria should be met first and how [13].…”

Section: Introductionmentioning

confidence: 99%

“…The previous work in the FAIR field addresses various aspects that lead to highquality datasets, such as focused nano-curation workflows, evaluation of the quality and completeness of curated data, and database integration [5]. Jacob et al [13] illustrated with experimental nano-data tables an approach (associated with a Design of Experiments) that can serve as a model for data management that enables data to be disseminated while meeting the FAIR criteria. Papadiamantis et al [5] provides two case studies; the first addresses dose metrics and the prediction of nanoparticles (NPs) agglomeration to determine a delivered dose that correlates with toxicity.…”

Section: Introductionmentioning

confidence: 99%

Data Shepherding in Nanotechnology. The Initiation

et al. 2021

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In this paper we describe the pragmatic approach of initiating, designing and implementing the Data Management Plan (DMP) and the data FAIRification process in the multidisciplinary Horizon 2020 nanotechnology project, Anticipating Safety Issues at the Design Stage of NAno Product Development (ASINA). We briefly describe the general DMP requirements, emphasizing that the initial steps in the direction towards data FAIRification must be conceptualized and visualized in a systematic way. We demonstrate the use of a generic questionnaire to capture primary data and metadata description from our consortium (data creators/experimentalists and data analysts/modelers). We then display the interactive process with external FAIR data initiatives (data curators/quality assessors), regarding guidance for data and metadata capturing and future integration into repositories. After the preliminary data capturing and FAIRification template is formed, the inner-communication process begins between the partners, which leads to developing case-specific templates. This paper assists future data creators, data analysts, stewards and shepherds engaged in the multi-faceted data shepherding process, in any project, by providing a roadmap, demonstrated in the case of ASINA.

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“…By their very heterogeneous nature, citizen science data are challenging to analyse ( Van Strien et al 2013 ). That is why it makes sense to integrate them into a database complying with the FAIR principles ( Wilkinson et al 2016 ) using a step-by-step community approach ( David et al 2020 ) and a pragmatic method taking into account the constraints of the stakeholders ( Jacob et al 2020 ). All of this is with the aim of promoting their sharing and dissemination within the scientific community interested in marine mammals and marine spatial planning.…”

Section: Introductionmentioning

confidence: 99%

Kakila database: Towards a FAIR community approved database of cetacean presence in the waters of the Guadeloupe Archipelago, based on citizen science

Coché¹,

Arnaud²,

Bouveret³

et al. 2021

BDJ

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In the French West Indies, more than 20 species of cetaceans have been observed over the last decades. The recognition of this hotspot of biodiversity of marine mammals, observed in the French Exclusive Economic Zone of the West Indies, motivated the French government to create in 2010 a marine protected area (MPA) dedicated to the conservation of marine mammals: the Agoa Sanctuary. Threats that cetacean populations face are multiple, but well-documented. Cetacean conservation can only be achieved if relevant and reliable data are available, starting by occurrence data. In the Guadeloupe Archipelago and in addition to some data collected by the Agoa Sanctuary, occurrence data are mainly available through the contribution of citizen science and of local stakeholders (i.e. non-profit organisations (NPO) and whale-watchers). However, no observation network has been coordinated and no standards exist for cetacean presence data collection and management. In recent years, several whale watchers and NPOs regularly collected cetacean observation data around the Guadeloupe Archipelago. Our objective was to gather datasets from three Guadeloupean whale watchers, two NPOs and the Agoa Sanctuary, that agreed to share their data. These heterogeneous data went through a careful process of curation and standardisation in order to create a new extended database, using a newly-designed metadata set. This aggregated dataset contains a total of 4,704 records of 21 species collected in the Guadeloupe Archipelago from 2000 to 2019. The database was called Kakila ("who is there?" in Guadeloupean Creole). The Kakila database was developed following the FAIR principles with the ultimate objective of ensuring sustainability. All these data were transferred into the PNDB repository (Pöle National de Données de Biodiversité, Biodiversity French Data Hub, https://www.pndb.fr). In the Agoa Sanctuary and surrounding waters, marine mammals have to interact with increasing anthropogenic pressure from growing human activities. In this context, the Kakila database fulfils the need for an organised system to structure marine mammal occurrences collected by multiple local stakeholders with a common objective: contribute to the knowledge and conservation of cetaceans living in the French Antilles waters. Much needed data analysis will enable us to identify high cetacean presence areas, to document the presence of rarer species and to determine areas of possible negative interactions with anthropogenic activities.

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Making experimental data tables in the life sciences more FAIR: a pragmatic approach

Cited by 12 publications

References 9 publications

Predictive metabolomics of multiple Atacama plant species unveils a core set of generic metabolites for extreme climate resilience

Predictive metabolomics of multiple Atacama plant species unveils a core set of generic metabolites for extreme climate resilience

Data Shepherding in Nanotechnology. The Initiation

Kakila database: Towards a FAIR community approved database of cetacean presence in the waters of the Guadeloupe Archipelago, based on citizen science

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