# Establishing Plankton Imagery Dataflows Towards International Biodiversity Data Aggregators

Patricia Martin-Cabrera, Ruben Perez Perez, Jean-Olivier Irrison, Fabien Lombard, Klas Ove Möller, Saskia Rühl, Veronique Creach, Markus Lindh, Lars Stemmann, Lennert Schepers

<figure><img src="image_1.png" /></figure>

To cite this version:

Patricia Martin-Cabrera, Ruben Perez Perez, Jean-Olivier Irrison, Fabien Lombard, Klas Ove Möller, et al.. Establishing Plankton Imagery Dataflows Towards International Biodiversity Data Aggregators. Biodiversity Information Science and Standards, 2022, 6, 10.3897/biss.6.94196. hal-03958791

HAL Id: hal-03958791

https://hal.science/hal-03958791

Submitted on 31 Mar 2023

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_2.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
Conference Abstract

# Establishing Plankton Imagery Dataflows Towards International Biodiversity Data Aggregators

Patricia Martin-Cabrera‡, Ruben Perez Perez‡, Jean-Olivier Irrison§, Fabien Lombard§, Klas Ove Möller¶, Saskia Rühl¶, Veronique Creach¶, Markus Lindh#, Lars Stemmann§, Lennert Schepers‡

‡ Flanders Marine Institute, Ostend, Belgium

§ Institut de la Mer de Villefranche, Centre National de la Recherche Scientifique – Sorbonne Université, Villefranche sur-Mer, France

| Institute of Carbon Cycles, Helmholtz-Zentrum Geesthacht, Hereon, Geesthacht, Germany

¶ Centre for Environment, Fisheries and Aquaculture Science, Lowestoft, United Kingdom

# Swedish Meteorological and Hydrological Institute, Västra Frölunda, Sweden

Corresponding author: Patricia Martin-Cabrera (patricia.cabrera@vliz.be)

Received: 29 Aug 2022 | Published: 07 Sep 2022

Citation: Martin-Cabrera P, Perez Perez R, Irrison J-O, Lombard F, Ove Möller K, Rühl S, Creach V, Lindh M, Stemmann L, Schepers L (2022) Establishing Plankton Imagery Dataflows Towards International Biodiversity Data Aggregators. Biodiversity Information Science and Standards 6: e94196.
https://doi.org/10.3897/biss.6.94196

## Abstract

Over the last decade, plankton research has experienced extensive developments in automatic image acquisition for identifying and quantifying plankton species. This information is useful for the reporting of plankton occurrences and ecological data. Imagery instruments can vary in the way they sample (benchtop or *in situ* imagers) and the particle's size range they target (see Lombard et al. (2019) for an extensive comparison of instruments and specifications). However, due to the wide variety of instruments and their (automatic) output data and formats, it is challenging to integrate datasets that originate from different sources. For this reason, we developed recommendations for plankton imagery data management, which can promote the ability to make these datasets as *FAIR* (Findable, Accessible, Interoperable and Reusable principles), as possible. The workflow presented here could inspire other Biodiversity Information Standards TDWG communities working with (automated) imagery data (e.g., camera traps) such as the *Audubon Core* and *Machine Observations* Interest Group.
The recommended data format follows the [OBIS-ENV-DATA](https://wwwOBIS.org/) format (De Pooter et al. 2017), a Darwin Core-based approach to standardise biodiversity data (Wieczorek et al. 2012) used in *EurOBIS*, the European node of the Ocean Biodiversity Information System (OBIS) and *EMODnet Biology*, the European Marine Biodiversity Data Network. However, this format does not include sufficient information for imagery data, therefore we propose the use of additional *Darwin Core terms*. For example, by including the terms *identifiedBy*, *identificationVerificationStatus* and *identificationReferences* in the Occurrence table, more clarity is reported regarding the uncertainty of the classification made by an algorithm. Thus, data providers can publish manually validated datasets or datasets produced by fully automated plankton identification workflows; and users can choose to use validated or not validated data. See in *Suppl. material 1* a practical example on how to report an imagery dataset following the best practices.

Moreover, the OBIS-ENV-DATA format allows the ingestion of additional information thanks to the use of the Darwin Core (DwC) [Extended Measurement Or Facts](https://wwwDwC.org/) or eMoF extension in the DwC Event core. The eMoF stores biotic, abiotic and sampling measurements and facts that are related to the Event and Occurrence table. An important aspect of this extension is that it includes standardised terms and controlled vocabularies, such as the British Oceanographic Data Centre (BODC) vocabularies, to standardise parameters that are not covered by DwC. The advantages of these is to unambiguously report information and to include those measurements that cannot be reported in the Event and Occurrence table (e.g., reporting abundance or biomass of plankton), and that are crucial to investigate ecosystem functioning questions. As a consequence, biodiversity data aggregators can extend their scope beyond species occurrence data.

Fig. 1 summarises a typical dataflow that goes from imagery data acquisition to publication in several steps:

1. Images are cropped and classified with software. This can be done in *EcoTaxa*, a web application that allows users to taxonomically classify images of individual organisms.

2. Data is formatted in OBIS-ENV-DATA format. This format can be exported from *EcoTaxa* through its [API](https://api.eo taxa.org/).

3. Data is submitted to EurOBIS via the [IPT](https://wwwi.nodc.noitte.com/IPT) (Integrated Publishing Toolkit).

4. Data is quality controlled by the [BioCheck tool](https://www.biotaxica.eu/BioCheck).

5. Data in EurOBIS can flow to EMODnet Biology, OBIS and [GBIF](https://www.gbi.fao.eu/) (Global Biodiversity Information Facility).

Plankton imagery instrument operators now have the possibility to format their data following the best practices and recommendations for plankton imagery data management (Martin-Cabrera et al. 2022). After a dataset is formatted following these guidelines, it can be submitted to the international biodiversity data aggregators, EurOBIS, EMODnet Biology and GBIF. Additionally a (semi) automated dataflow is presented where data
providers can classify images in EcoTaxa and export the data in the required formats using
an API before submission to EurOBIS.

The next steps are to disseminate these best practices, encouraging plankton imagery
data generators to implement these workflows to share their data easily, enriching these
data portals and encouraging cross collaborations to create data products covering
broader geographic scales and plankton species.

<figure><img src="image_3.png" /><figcaption>Figure 1.</figcaption></figure>

Complete workflow from imagery instrument to international biodiversity data aggregators.

Keywords

imagery instruments, imagery data, Darwin Core, best practices

Presenting author

Patricia Martin-Cabrera

Presented at

TDWG 2022

Acknowledgements

This work was supported by the JERICO-S3 project, that received funding from the
European Union's Horizon 2020 research and innovation programme, grant agreement no.
871153.
## Hosting institution

Flanders Marine Institute

## References

* De Pooter D, Appeltans W, Bailly N, Bristol S, Deneudt K, Eliezer M, Fujioka E, Giorgetti A, Goldstein P, Lewis M, Lipizer M, Mackay K, Marin M, Moncoiffé G, Nikolopoulou S, Provoost P, Rauch S, Roubicek A, Torres C, van de Putte A, Vandepitte L, Vanhoorne B, Vinci M, Wambiji N, Watts D, Klein Salas E, Hernandez F (2017) Toward a new data standard for combined marine biological and environmental datasets - expanding OBIS beyond species occurrences. Biodiversity Data Journal 5: e10989. https://doi.org/10.3897/bdj.5.e10989

* Lombard F, Boss E, Waite A, Vogt M, Uitz J, Stemmann L, Sosik H, Schulz J, Romagnan J, Picheral M, Pearlman J, Ohman M, Niehoff B, Möller K, Miloslavich P, Lara-Lpez A, Kudela R, Lopes R, Kiko R, Karp-Boss L, Jaffe J, Iversen M, Irisson J, Fennel K, Hauss H, Guidi L, Gorsky G, Giering SC, Gaube P, Gallager S, Dubelaar G, Cowen R, Carlotti F, Briseño-Avena C, Berline L, Benoit-Bird K, Bax N, Batten S, Ayata SD, Artigas LF, Appeltans W (2019) Globally Consistent Quantitative Observations of Planktonic Ecosystems. Frontiers in Marine Science 6: 196. https://doi.org/10.3389/fmars.2019.00196

* Martin-Cabrera P, Perez Perez R, Irisson J, Lombard F, F. MO, Rühl S, Creach V, Lindh M, Stemmann L, Schepers L (2022) Best practices and recommendations for plankton imagery data management: Ensuring effective data flow towards European data infrastructures. Flanders Marine Institute, VLIZ, Ostend. 31 pp. https://doi.org/10.25607/OBP-1742

* Wieczorek J, Bloom D, Guralnick R, Blum S, Döring M, Giovanni R, Robertson T, Vieglais D (2012) Darwin Core: An Evolving Community-Developed Biodiversity Data Standard. PLoS ONE 7 (1):29715. https://doi.org/10.1371/journal.pone.0029715

## Supplementary material

### Suppl. material 1: Imagery dataset example doi

**Authors:** Patricia Martin-Cabrera

**Data type:** Imagery data

**Brief description:** Practical example of the data format proposed for plankton imagery data

Download file (251.34 kb)