ArticleScientific data2023
The benefits and struggles of FAIR data: the case of reusing plant phenotyping data.
Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- Fruit and Vegetable By-Products as Postharvest Tissue Fractions: A Raw-Material Framework for Plant-Based Food Development.Plants (Basel, Switzerland) · 2026Review
- Omics-driven plant breeding through phenomics-enviromics crosstalk.Nature communications · 2026Review
- Beyond Data: Artificial intelligence, knowledge graphs, and the next revolution in wheat breeding.Plant communications · 2026Review
- CartograPlant: bridging genomic, phenotypic, and environmental data to advance plant resilience and eco-evolutionary insight.Genetics · 2026Article
- Improving annotation, access, and comparison of nutritional composition data for underutilized crops.Database : the journal of biological databases and curation · 2026Article
- Harnessing the untapped genetic diversity of local landraces: omics technologies as a gateway to horticultural breeding.Frontiers in plant science · 2026Review
- Longitudinal dataset of journal data sharing policies across 22 disciplines for 2014 2019 and 2023.Scientific data · 2025Article
- Order from entropy: big data from FAIR data cohorts in the digital age of plant breeding.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Review
- Artificial intelligence in plant science: from image-based phenotyping to yield and trait prediction.Frontiers in plant science · 2025Review
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Plant phenotyping experiments are conducted under a variety of experimental parameters and settings for diverse purposes. The data they produce is heterogeneous, complicated, often poorly documented and, as a result, difficult to reuse. Meeting societal needs (nutrition, crop adaptation and stability) requires more efficient methods toward data integration and reuse. In this work, we examine what "making data FAIR" entails, and investigate the benefits and the struggles not only of reusing FAIR data, but also making data FAIR using genotype by environment and QTL by environment interactions for developmental traits in potato as a case study. We assume the role of a scientist discovering a phenotypic dataset on a FAIR data point, verifying the existence of related datasets with environmental data, acquiring both and integrating them. We report and discuss the challenges and the potential for reusability and reproducibility of FAIRifying existing datasets, using metadata standards such as MIAPPE, that were encountered in this process.
Indexed as
Identifiers
What OpenQuestion holds
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.