Paving the way for FAIR data in plant phenotyping

The increasing nutritional demands of the world as well as the need for crops that perform reliably, in spite of diverse environmental conditions (abiotic and biotic stresses and variable weather conditions), put the plant sciences at the forefront of domains where progress is urgently needed. To be able to do so, plant phenotyping and genotyping are extremely important. Especially in plant phenotyping, research is met with challenges related to poor data management, and thereby inefficient exploitation - let alone reuse of datasets. The challenges to phenotypic data reuse and integration arise due to the highly distributed nature of data in the domain (as there are no central plant phenotypic data repositories) and their multifaceted heterogeneity. The variety of experimental goals and the sheer number of species studied may necessitate different approaches (e.g. for crops, model organisms, forest trees). Experiments may be conducted in open fields, greenhouses or other locations, follow different designs and produce different types of data (e.g. visual observation of a score, images, manual and automatic measurements, molecular assays). Even when everything else matches, the data files produced may have different formats and structures, which is a challenge for data integration. Moreover, good data documentation practices are often lacking, which hinders interpretation and reuse. In the vast majority of cases, plant phenotyping datasets are used only once, solely to address the research question for which they were originally generated. It is the exception, rather than the rule, when different datasets, produced by different, uncoordinated parties, are analyzed to generate further knowledge. Even rarer, though much more useful, are cases where independently created datasets are integrated for the purpose of meta-analyses or improvement of statistical and predictive models. Such work is crucial, for example, for multi-environment studies investigating the adaptabil