Project
Advances in data-driven phenotyping
It is a challenge to properly record the enormous increase in genotypic and phenotypic data with the characteristics and performance of plants in all kinds of experiments in systems in accordance with the guidelines of FAIR data. In addition, a collective approach is needed to also share the knowledge and tools for the analysis with other researchers.
One of the biggest challenges for data science is the accessibility and reusability of data that are collected for specific research purposes. These data contain often (sensitive) information from external parties, are collected to answer specific research questions, and where it can be unclear whether the data can be used for other purposes too. This is highly relevant to know, because these data can be valuable for multidisciplinary research that often cover complex societal issues.
There is a strong intensive debate going on with respect to data ownership, especially when these data are generated at and/or by agricultural enterprises, or when these data are collected for the purpose of food safety. However, sharing of these (sensitive) data, required to conduct multidisciplinary research, is in its infancy. This project aims at developing a shared, domain overarching, and privacy-conserving infrastructure that enables safe, efficient, and controlled mechanisms to share or re-use these data. This infrastructure will stimulate activities to integrate these data within WUR, and ultimately also outside WUR, and support scientific data-driven research where data ownership and privacy issues will be guaranteed. We will work towards this goal by exploring the possibility to connect infrastructures at different science groups, as well as the collection of data generated on-farm. The project runs from 2019 till 2022.
Publicaties
-
Hotspot Vegetation Structure and Terrain Monitoring of Dutch Coastal Dunes with LiDAR and Optical Camera's Mounted on Drones
In: 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS - IEEE - ISBN: 9781665447621 - p. 739-742. -
Equivalence tests for safety assessment of genetically modified crops using plant composition data
Food and Chemical Toxicology (2021), Volume: 156 - ISSN 0278-6915 -
Phenotyping with drones : An overview of activities
-
Multivariate equivalence testing for food safety assessment
Food and Chemical Toxicology (2022), Volume: 170 - ISSN 0278-6915