ArticlePlant phenomics (Washington, D.C.)2019
Applying FAIR Principles to Plant Phenotypic Data Management in GnpIS.
Article in Plant phenomics (Washington, D.C.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
22 citing papers in PubMed.
- PhenoRob-P: An autonomous robotic system for high-throughput phenotyping of potted plants.Plant phenomics (Washington, D.C.) · 2026Article
- Wheat historical phenotypic data from European genebanks as an important resource for research and breeding.Scientific data · 2026Article
- Improving annotation, access, and comparison of nutritional composition data for underutilized crops.Database : the journal of biological databases and curation · 2026Article
- Improving plant breeding through AI-supported data integration.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Review
- BrAPI v2: real-world applications for data integration and collaboration in the breeding and genetics community.Database : the journal of biological databases and curation · 2025Article
- Genotype and phenotype data standardization, utilization and integration in the big data era for agricultural sciences.Database : the journal of biological databases and curation · 2023Review
- Pitfalls and potential of high-throughput plant phenotyping platforms.Frontiers in plant science · 2023Article
- The potential of integrative phenomics to harness underutilized crops for improving stress resilience.Frontiers in plant science · 2023Article
- Proximal and remote sensing in plant phenomics: 20 years of progress, challenges, and perspectives.Plant communications · 2022Review
- Centralized project-specific metadata platforms: toolkit provides new perspectives on open data management within multi-institution and multidisciplinary research projects.BMC research notes · 2022Article
- High-throughput field crop phenotyping: current status and challenges.Breeding science · 2022Article
- Breeding for Economically and Environmentally Sustainable Wheat Varieties: An Integrated Approach from Genomics to Selection.Biology · 2022Review
- BioSamples database: FAIRer samples metadata to accelerate research data management.Nucleic acids research · 2022Article
- ELIXIR: providing a sustainable infrastructure for life science data at European scale.Bioinformatics (Oxford, England) · 2021Article
- Data management challenges for artificial intelligence in plant and agricultural research.F1000Research · 2021Article
- The Ontologies Community of Practice: A CGIAR Initiative for Big Data in Agrifood Systems.Patterns (New York, N.Y.) · 2020Article
- Enabling reusability of plant phenomic datasets with MIAPPE 1.1.The New phytologist · 2020Article
- Cyberinfrastructure and resources to enable an integrative approach to studying forest trees.Evolutionary applications · 2020Article
- Editorial: Phenotyping; From Plant, to Data, to Impact and Highlights of the International Plant Phenotyping Symposium - IPPS 2018.Frontiers in plant science · 2020Article
- MVS-Pheno: A Portable and Low-Cost Phenotyping Platform for Maize Shoots Using Multiview Stereo 3D Reconstruction.Plant phenomics (Washington, D.C.) · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
20 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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,
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.