Dealing with multi-source and multi-scale information in plant phenomics: the ontology-driven Phenotyping Hybrid Information System

Autor: François Tardieu, Romain Chapuis, Vincent Negre, Jonathan Mineau-Cesari, Brigitte Charnomordic, Nadine Hilgert, Isabelle Sanchez, Pascal Neveu, Anne Tireau, Nicolas Brichet, Cyril Pommier, Llorenç Cabrera-Bosquet
Přispěvatelé: Mathématiques, Informatique et STatistique pour l'Environnement et l'Agronomie (MISTEA), Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro), Domaine expérimental de Melgueil (MONTP MELGUEIL UE), Institut National de la Recherche Agronomique (INRA), Unité de Recherche Génomique Info (URGI), 'Infrastructure Biologie Sante' PHENOME-EMPHASIS project, 'Programme d'Investissements d'Avenir' (PIA), ANR-11-INBS-0012,PHENOME,Centre français de phénomique végétale(2011)
Rok vydání: 2018
Předmět:
0106 biological sciences
0301 basic medicine
knowledge
Databases
Factual
Physiology
Computer science
[SDV]Life Sciences [q-bio]
Method
interoperability
Plant Science
Information System
Ontology (information science)
computer.software_genre
01 natural sciences
Plot (graphics)
Field (computer science)
Workflow
User-Computer Interface
03 medical and health sciences
Phenomics
open source
Methods
Information system
[SDV.BV]Life Sciences [q-bio]/Vegetal Biology
[INFO]Computer Science [cs]
ontology
[MATH]Mathematics [math]
data integration
Data Curation
Internet
Information retrieval
Research
Data Visualization
phenomics
Plants
Metadata
Phenotype
030104 developmental biology
Biological Ontologies
système d'information
[SDE]Environmental Sciences
sélection phénomique
data science
Web service
computer
Information Systems
010606 plant biology & botany
Data integration
Zdroj: New Phytologist
New Phytologist, Wiley, 2019, 221 (1), pp.588-601. ⟨10.1111/nph.15385⟩
New Phytologist 1 (221), 588-601. (2019)
The New Phytologist
ISSN: 0028-646X
1469-8137
DOI: 10.1111/nph.15385
Popis: International audience; Summary : . Phenomic datasets need to be accessible to the scientific community. Their reanalysis requires tracing relevant information on thousands of plants, sensors and events. . The open-source Phenotyping Hybrid Information System (PHIS) is proposed for plant phenotyping experiments in various categories of installations (field, glasshouse). It unambiguously identifies all objects and traits in an experiment and establishes their relations via ontologies and semantics that apply to both field and controlled conditions. For instance, the genotype is declared for a plant or plot and is associated with all objects related to it. Events such as successive plant positions, anomalies and annotations are associated with objects so they can be easily retrieved. . Its ontology-driven architecture is a powerful tool for integrating and managing data from multiple experiments and platforms, for creating relationships between objects and enriching datasets with knowledge and metadata. It interoperates with external resources via web services, thereby allowing data integration into other systems; for example, modelling platforms or external databases. . It has the potential for rapid diffusion because of its ability to integrate, manage and visualize multi-source and multi-scale data, but also because it is based on 10 yr of trial and error in our groups.
Databáze: OpenAIRE
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