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Mosquito alert: leveraging citizen science to create a GBIF mosquito occurrence dataset
The Mosquito Alert dataset includes occurrence records of adult mosquitoes collected worldwide in 2014–2020 through Mosquito Alert, a citizen science system for investigating and managing disease-carrying mosquitoes. Records are linked to citizen science-submitted photographs and validated by entomo...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
GigaScience Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9930537/ https://www.ncbi.nlm.nih.gov/pubmed/36824520 http://dx.doi.org/10.46471/gigabyte.54 |
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author | Južnič-Zonta, Živko Sanpera-Calbet, Isis Eritja, Roger Palmer, John R.B. Escobar, Agustí Garriga, Joan Oltra, Aitana Richter-Boix, Alex Schaffner, Francis della Torre, Alessandra Miranda, Miguel Ángel Koopmans, Marion Barzon, Luisa Bartumeus Ferre, Frederic |
author_facet | Južnič-Zonta, Živko Sanpera-Calbet, Isis Eritja, Roger Palmer, John R.B. Escobar, Agustí Garriga, Joan Oltra, Aitana Richter-Boix, Alex Schaffner, Francis della Torre, Alessandra Miranda, Miguel Ángel Koopmans, Marion Barzon, Luisa Bartumeus Ferre, Frederic |
author_sort | Južnič-Zonta, Živko |
collection | PubMed |
description | The Mosquito Alert dataset includes occurrence records of adult mosquitoes collected worldwide in 2014–2020 through Mosquito Alert, a citizen science system for investigating and managing disease-carrying mosquitoes. Records are linked to citizen science-submitted photographs and validated by entomologists to determine the presence of five targeted European mosquito vectors: Aedes albopictus, Ae. aegypti, Ae. japonicus, Ae. koreicus, and Culex pipiens. Most records are from Spain, reflecting Spanish national and regional funding, but since autumn 2020 substantial records from other European countries are included, thanks to volunteer entomologists coordinated by the AIM-COST Action, and to technological developments to increase scalability. Among other applications, the Mosquito Alert dataset will help develop citizen science-based early warning systems for mosquito-borne disease risk. It can also be reused for modelling vector exposure risk, or to train machine-learning detection and classification routines on the linked images, to assist with data validation and establishing automated alert systems. |
format | Online Article Text |
id | pubmed-9930537 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | GigaScience Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-99305372023-02-22 Mosquito alert: leveraging citizen science to create a GBIF mosquito occurrence dataset Južnič-Zonta, Živko Sanpera-Calbet, Isis Eritja, Roger Palmer, John R.B. Escobar, Agustí Garriga, Joan Oltra, Aitana Richter-Boix, Alex Schaffner, Francis della Torre, Alessandra Miranda, Miguel Ángel Koopmans, Marion Barzon, Luisa Bartumeus Ferre, Frederic GigaByte Data Release The Mosquito Alert dataset includes occurrence records of adult mosquitoes collected worldwide in 2014–2020 through Mosquito Alert, a citizen science system for investigating and managing disease-carrying mosquitoes. Records are linked to citizen science-submitted photographs and validated by entomologists to determine the presence of five targeted European mosquito vectors: Aedes albopictus, Ae. aegypti, Ae. japonicus, Ae. koreicus, and Culex pipiens. Most records are from Spain, reflecting Spanish national and regional funding, but since autumn 2020 substantial records from other European countries are included, thanks to volunteer entomologists coordinated by the AIM-COST Action, and to technological developments to increase scalability. Among other applications, the Mosquito Alert dataset will help develop citizen science-based early warning systems for mosquito-borne disease risk. It can also be reused for modelling vector exposure risk, or to train machine-learning detection and classification routines on the linked images, to assist with data validation and establishing automated alert systems. GigaScience Press 2022-05-30 /pmc/articles/PMC9930537/ /pubmed/36824520 http://dx.doi.org/10.46471/gigabyte.54 Text en © The Author(s) 2022. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Data Release Južnič-Zonta, Živko Sanpera-Calbet, Isis Eritja, Roger Palmer, John R.B. Escobar, Agustí Garriga, Joan Oltra, Aitana Richter-Boix, Alex Schaffner, Francis della Torre, Alessandra Miranda, Miguel Ángel Koopmans, Marion Barzon, Luisa Bartumeus Ferre, Frederic Mosquito alert: leveraging citizen science to create a GBIF mosquito occurrence dataset |
title | Mosquito alert: leveraging citizen science to create a GBIF mosquito occurrence dataset |
title_full | Mosquito alert: leveraging citizen science to create a GBIF mosquito occurrence dataset |
title_fullStr | Mosquito alert: leveraging citizen science to create a GBIF mosquito occurrence dataset |
title_full_unstemmed | Mosquito alert: leveraging citizen science to create a GBIF mosquito occurrence dataset |
title_short | Mosquito alert: leveraging citizen science to create a GBIF mosquito occurrence dataset |
title_sort | mosquito alert: leveraging citizen science to create a gbif mosquito occurrence dataset |
topic | Data Release |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9930537/ https://www.ncbi.nlm.nih.gov/pubmed/36824520 http://dx.doi.org/10.46471/gigabyte.54 |
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