Applying FAIR Principles to Plant Phenotypic Data Management in GnpIS

GnpIS is a data repository for plant phenomics that stores whole field and greenhouse experimental data including environment measures. It allows long-term access to datasets following the FAIR principles: Findable, Accessible, Interoperable, and Reusable, by using a flexible and original approach....

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Main Authors: C. Pommier, C. Michotey, G. Cornut, P. Roumet, E. Duchêne, R. Flores, A. Lebreton, M. Alaux, S. Durand, E. Kimmel, T. Letellier, G. Merceron, M. Laine, C. Guerche, M. Loaec, D. Steinbach, M. A. Laporte, E. Arnaud, H. Quesneville, A. F. Adam-Blondon
Format: Article
Language:English
Published: American Association for the Advancement of Science (AAAS) 2019-01-01
Series:Plant Phenomics
Online Access:http://dx.doi.org/10.34133/2019/1671403
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author C. Pommier
C. Michotey
G. Cornut
P. Roumet
E. Duchêne
R. Flores
A. Lebreton
M. Alaux
S. Durand
E. Kimmel
T. Letellier
G. Merceron
M. Laine
C. Guerche
M. Loaec
D. Steinbach
M. A. Laporte
E. Arnaud
H. Quesneville
A. F. Adam-Blondon
author_facet C. Pommier
C. Michotey
G. Cornut
P. Roumet
E. Duchêne
R. Flores
A. Lebreton
M. Alaux
S. Durand
E. Kimmel
T. Letellier
G. Merceron
M. Laine
C. Guerche
M. Loaec
D. Steinbach
M. A. Laporte
E. Arnaud
H. Quesneville
A. F. Adam-Blondon
author_sort C. Pommier
collection DOAJ
description GnpIS is a data repository for plant phenomics that stores whole field and greenhouse experimental data including environment measures. It allows long-term access to datasets following the FAIR principles: Findable, Accessible, Interoperable, and Reusable, by using a flexible and original approach. It is based on a generic and ontology driven data model and an innovative software architecture that uncouples data integration, storage, and querying. It takes advantage of international standards including the Crop Ontology, MIAPPE, and the Breeding API. GnpIS allows handling data for a wide range of species and experiment types, including multiannual perennial plants experimental network or annual plant trials with either raw data, i.e., direct measures, or computed traits. It also ensures the integration and the interoperability among phenotyping datasets and with genotyping data. This is achieved through a careful curation and annotation of the key resources conducted in close collaboration with the communities providing data. Our repository follows the Open Science data publication principles by ensuring citability of each dataset. Finally, GnpIS compliance with international standards enables its interoperability with other data repositories hence allowing data links between phenotype and other data types. GnpIS can therefore contribute to emerging international federations of information systems.
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spelling doaj.art-e014a977ad414fd2af093f01e75dafb62022-12-21T17:26:00ZengAmerican Association for the Advancement of Science (AAAS)Plant Phenomics2643-65152019-01-01201910.34133/2019/1671403Applying FAIR Principles to Plant Phenotypic Data Management in GnpISC. Pommier0C. Michotey1G. Cornut2P. Roumet3E. Duchêne4R. Flores5A. Lebreton6M. Alaux7S. Durand8E. Kimmel9T. Letellier10G. Merceron11M. Laine12C. Guerche13M. Loaec14D. Steinbach15M. A. Laporte16E. Arnaud17H. Quesneville18A. F. Adam-Blondon19URGI, INRA, Université Paris-Saclay, 78026 Versailles, FranceURGI, INRA, Université Paris-Saclay, 78026 Versailles, FranceURGI, INRA, Université Paris-Saclay, 78026 Versailles, FranceAGAP, Univ Montpellier, CIRAD, INRA, Montpellier SupAgro, Montpellier, FranceUMR SVQV, 28 rue de Herrlisheim, B.P. 20507, 68021 Colmar, FranceURGI, INRA, Université Paris-Saclay, 78026 Versailles, FranceURGI, INRA, Université Paris-Saclay, 78026 Versailles, FranceURGI, INRA, Université Paris-Saclay, 78026 Versailles, FranceURGI, INRA, Université Paris-Saclay, 78026 Versailles, FranceURGI, INRA, Université Paris-Saclay, 78026 Versailles, FranceURGI, INRA, Université Paris-Saclay, 78026 Versailles, FranceURGI, INRA, Université Paris-Saclay, 78026 Versailles, FranceURGI, INRA, Université Paris-Saclay, 78026 Versailles, FranceURGI, INRA, Université Paris-Saclay, 78026 Versailles, FranceURGI, INRA, Université Paris-Saclay, 78026 Versailles, FranceURGI, INRA, Université Paris-Saclay, 78026 Versailles, FranceBioversity International, parc Scientifique Agropolis II, 34397 Montpellier cedex 5, FranceBioversity International, parc Scientifique Agropolis II, 34397 Montpellier cedex 5, FranceURGI, INRA, Université Paris-Saclay, 78026 Versailles, FranceURGI, INRA, Université Paris-Saclay, 78026 Versailles, FranceGnpIS is a data repository for plant phenomics that stores whole field and greenhouse experimental data including environment measures. It allows long-term access to datasets following the FAIR principles: Findable, Accessible, Interoperable, and Reusable, by using a flexible and original approach. It is based on a generic and ontology driven data model and an innovative software architecture that uncouples data integration, storage, and querying. It takes advantage of international standards including the Crop Ontology, MIAPPE, and the Breeding API. GnpIS allows handling data for a wide range of species and experiment types, including multiannual perennial plants experimental network or annual plant trials with either raw data, i.e., direct measures, or computed traits. It also ensures the integration and the interoperability among phenotyping datasets and with genotyping data. This is achieved through a careful curation and annotation of the key resources conducted in close collaboration with the communities providing data. Our repository follows the Open Science data publication principles by ensuring citability of each dataset. Finally, GnpIS compliance with international standards enables its interoperability with other data repositories hence allowing data links between phenotype and other data types. GnpIS can therefore contribute to emerging international federations of information systems.http://dx.doi.org/10.34133/2019/1671403
spellingShingle C. Pommier
C. Michotey
G. Cornut
P. Roumet
E. Duchêne
R. Flores
A. Lebreton
M. Alaux
S. Durand
E. Kimmel
T. Letellier
G. Merceron
M. Laine
C. Guerche
M. Loaec
D. Steinbach
M. A. Laporte
E. Arnaud
H. Quesneville
A. F. Adam-Blondon
Applying FAIR Principles to Plant Phenotypic Data Management in GnpIS
Plant Phenomics
title Applying FAIR Principles to Plant Phenotypic Data Management in GnpIS
title_full Applying FAIR Principles to Plant Phenotypic Data Management in GnpIS
title_fullStr Applying FAIR Principles to Plant Phenotypic Data Management in GnpIS
title_full_unstemmed Applying FAIR Principles to Plant Phenotypic Data Management in GnpIS
title_short Applying FAIR Principles to Plant Phenotypic Data Management in GnpIS
title_sort applying fair principles to plant phenotypic data management in gnpis
url http://dx.doi.org/10.34133/2019/1671403
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