SYKE-plankton_IFCB_2022

DOI

The data set available here is published along with an article “Kraft et al. (2022). Towards operational phytoplankton recognition with automated high-throughput imaging, near real-time data processing, and convolutional neural networks. Front Mar. Sci. 9. Doi: 10.3389/fmars.2022.867695” and if used for further purposes, the article should be cited accordingly. The data set contains approximately 63 000 images belonging to 50 different classes, consisting mainly of phytoplankton. The images can be used to e.g. train a classifier to identify phytoplankton images.

The images were collected with an Imaging FlowCytobot (IFCB, McLane Research Laboratories, Inc., U.S., Olson and Sosik, 2007) from different locations in the Baltic Sea. In 2017 and 2018 the data were collected from a continuous deployment at the Utö Atmospheric and Marine Research Station (59°46.84’ N, 21°22.13’ E; Laakso et al., 2018; Kraft et al., 2021) operated by Finnish Environment Institute and Finnish Meteorological Institute (n=62). In 2016 and 2019 water samples were collected using the Alg@line ferrybox systems of M/S Finnmaid and Silja Serenade (Ruokanen et al., 2003; Kaitala et al., 2014) and manually ran in the laboratory (n=52). The images were manually annotated by expert taxonomists. The class list and labeled image set is a continuous work in progress, thus there may be a need for revision in future. The data set available with this doi will not be revised. More detailed explanation and example images can be found from the publication Kraft et al. 2022.

The zipped folder contains 50 different folders, and the images are located in the class-specific folders. The image names may refer to an old class (e.g. folder Cryptophyceae-Teleaulax contains images with names Cryptophyceae_drop, Cryptophyceae_small, Teleaulax sp.) that has been joined with another one / revised otherwise.

The work utilized SYKE and FMI marine research infrastructure as a part of the national FINMARI RI consortium. The work was partly funded by Tiina and Antti Herlin Foundation (personal grant for KK), Academy of Finland project FASTVISION (grant no. 321980), Academy of Finland project FASTVISION-plus (grant no. 339355), JERICO-S3 project, funded by the European Commission’s H2020 Framework Programme under grant agreement No. 871153, and PHIDIAS project, funded by the European Union's Connecting Europe Facility under grant agreement INEA/CEF/ICT/A2018/1810854.

The class list separated in taxonomic groups

Cyanophyceae Aphanizomenon flosaquae Aphanothece paralleliformis Chroococcales Chroococcus sp. Dolichospermum sp. / Anabaenopsis sp. Dolichospermum sp. / Anabaenopsis sp. coiled Merismopedia sp. Nodularia spumigena Oscillatoriales Snowella sp. / Woronichinia sp.

Cryptophyceae Cryptomonadales Cryptophyceae / Teleaulax sp.

Euglenophyceae Euglenophyceae Eutreptiella sp.

Dinophyceae Amylax triacantha Dinophyceae Dinophysis acuminata Gonyaulax verior Gymnodiniales Gymnodinium like cells Heterocapsa rotundata Heterocapsa triquetra Peridiniella catenata chain Peridiniella catenata single Prorocentrum cordatum

Diatomophyceae Centrales Ceratoneis closterium Chaetoceros sp. chain Chaetoceros sp. single Cyclotella choctawhatcheeana Licmophora sp. Melosira arctica Nitzschia paleacea Pauliella taeniata Pennales thick Pennales thin Skeletonema marinoi Thalassiosira levanderi

Chrysophyceae Pseudopedinella sp. Uroglenopsis sp.

Chlorophyta Chlorococcales Cymbomonas tetramitiformis Monoraphidium contortum Oocystis sp. Pyramimonas sp.

Other Katablepharis remigera

Ciliates Ciliata Mesodinium rubrum

Additional classes Beads Heterocyte

Identifier
DOI https://doi.org/10.23728/b2share.abf913e5a6ad47e6baa273ae0ed6617a
Source https://b2share.eudat.eu/records/abf913e5a6ad47e6baa273ae0ed6617a
Related Identifier http://doi.org/10.23728/b2share.7c273b6f409c47e98a868d6517be3ae3
Metadata Access https://b2share.eudat.eu/api/oai2d?verb=GetRecord&metadataPrefix=eudatcore&identifier=oai:b2share.eudat.eu:b2rec/abf913e5a6ad47e6baa273ae0ed6617a
Provenance
Creator Kraft, Kaisa; Velhonoja, Otso; Seppälä, Jukka; Hällfors, Heidi; Suikkanen, Sanna; Ylöstalo, Pasi; Anglès, Sílvia; Kielosto, Sami; Kuosa, Harri; Lehtinen, Sirpa; Oja, Johanna; Tamminen, Timo
Instrument Imaging FlowCytobot
Publisher EUDAT B2SHARE
Contributor Finnish Environment Institute
Publication Year 2022
Funding Reference Academy of Finland 321980; European Commission’s H2020 Framework Programme 871153; European Union's Connecting Europe Facility INEA/CEF/ICT/A2018/1810854; Tiina and Antti Herlin Foundation; FINMARI RI consortium; Academy of Finland 339355
Rights Creative Commons Attribution (CC-BY); info:eu-repo/semantics/openAccess
OpenAccess true
Contact kaisa.kraft(at)syke.fi, jukka.seppala(at)syke.fi, finmari-data(at)syke.fi
Representation
Resource Type Dataset
Format zip; pdf
Size 509.3 MB; 2 files
Discipline 3.1.21 → Biology → Marine biology