VLIZ observatory data: an R Shiny application for validation of biodiversity observations from imaging sensors
Citation
Mortelmans, J. (2026). jonasmortelmansvliz/ImagingValidationApp: v1.0.1 (v1.0.1). Zenodo. https://doi.org/10.5281/zenodo.18429119
https://doi.org/10.5281/zenodo.18429119 Contact:
Mortelmans, Jonas Availability:
This dataset is licensed under a Creative Commons Attribution 4.0 International License.Description
Imaging sensors are widely used in marine observatories to collect biodiversity observations, but image-based data typically require manual validation before further use. We present an R Shiny application developed within the VLIZ observatory framework to support the validation of biodiversity observations derived from imaging sensors. The application allows users to browse large sets of images organised in folders, visually inspect individual images, and assign validation or annotation labels using a predefined taxonomy. Images can be labeled individually or in bulk. Validated results are stored in a simple tabular format with user attribution and can be exported for integration into downstream workflows. The application is sensor-independent and can be applied to image data from different imaging platforms, providing a practical tool for routine validation of imaging-based biodiversity observations. moreImagingValidationApp is an interactive Shiny application designed to: (1) Browse .tif plankton images in subfolders; (2) Select images and assign labels based on taxonomy; (3) Track progress for each subfolder and overall dataset and (4) Export validated labels to CSV files for downstream analysis The app dynamically generates label buttons based on a taxonomy file and color-codes them according to type (e.g., detritus, phytoplankton, copepod)
Contributors
Vlaams Instituut voor de Zee (VLIZ), more, data owner, data creator, owner
Related datasets
Parent dataset: VLIZ observatory data: shipboard underway plankton biodiversity observations by flow-through imaging (Plankton Imager, Pi-10) in the Southern North Sea, more Dataset status: In Progress
Data type: Software/models/scripts
Data origin: Research: field survey
Metadatarecord created: 2026-01-30
Information last updated: 2026-01-30
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