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LifeWatch observatory data: phytoplankton observations in the Belgian Part of the North Sea
Amadei Martínez, L.; Mortelmans, J.; Dillen, N.; Debusschere, E.; Deneudt, K. (2020). LifeWatch observatory data: phytoplankton observations in the Belgian Part of the North Sea. Biodiversity Data Journal 8: e57236. https://dx.doi.org/10.3897/bdj.8.e57236
In: Biodiversity Data Journal. Pensoft Publishers: Sofia. ISSN 1314-2836; e-ISSN 1314-2828
Is gerelateerd aan:
Amadei Martínez, L.; Mortelmans, J.; Dillen, N.; Debusschere, E.; Deneudt, K. (2022). Corrigendum to "LifeWatch observatory data: phytoplankton observations in the Belgian Part of the North Sea". Biodiversity Data Journal 10: e81208, meer
Peer reviewed article  

Beschikbaar in  Auteurs 

Trefwoord
    Marien/Kust
Author keywords
    phytoplankton, Belgium, marine, LifeWatch Belgium, FlowCAM, image recognition

Auteurs  Top 
  • Amadei Martínez, L.
  • Mortelmans, J.
  • Dillen, N.
  • Debusschere, E.
  • Deneudt, K., meer

Abstract

    Background

    This paper describes a phytoplankton data series generated through systematic observations in the Belgian Part of the North Sea (BPNS). Phytoplankton samples were collected during multidisciplinary sampling campaigns, visiting nine nearshore stations with monthly frequency and an additional eight offshore stations on a seasonal basis.

    New information

    The data series contain taxon-specific phytoplankton densities determined by analysis with the Flow Cytometer And Microscope (FlowCAM®) and associated image-based classification. The classification is performed by two separate semi-automated classification systems, followed by manual validation by taxonomic experts. To date, 637,819 biological particles have been collected and identified, yielding a large dataset of validated phytoplankton images. The collection and processing of the 2017–2018 dataset are described, along with its data curation, quality control and data storage. In addition, the classification of images using image classification algorithms, based on convolutional neural networks (CNN) from 2019 onwards, is also described. Data are published in a standardised format together with environmental parameters, accompanied by extensive metadata descriptions and finally labelled with digital identifiers for traceability. The data are published under a CC‐BY 4.0 licence, allowing the use of the data under the condition of providing the reference to the source.


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