GLOBE Observer: A Case Study in Advancing Earth System Knowledge with AI-Powered Citizen Science
Citizen science and artificial intelligence (AI) complement each other by harnessing the strengths of both human and machine capabilities. Citizen science generates terabytes of raw numerical, text, and image data, the analysis of which requires automated techniques to process in an efficient manner...
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| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Ubiquity Press
2024-12-01
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| Series: | Citizen Science: Theory and Practice |
| Subjects: | |
| Online Access: | https://account.theoryandpractice.citizenscienceassociation.org/index.php/up-j-cstp/article/view/747 |
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| _version_ | 1841554973218832384 |
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| author | Peder V. Nelson Russanne Low Holli Kohl David Overoye Di Yang Xiao Huang Sriram Chellappan Farhat Binte Azam Ryan M. Carney Monika Falk Joan Garriga Larisa Schelkin Rebecca Boger Theresa Schwerin |
| author_facet | Peder V. Nelson Russanne Low Holli Kohl David Overoye Di Yang Xiao Huang Sriram Chellappan Farhat Binte Azam Ryan M. Carney Monika Falk Joan Garriga Larisa Schelkin Rebecca Boger Theresa Schwerin |
| author_sort | Peder V. Nelson |
| collection | DOAJ |
| description | Citizen science and artificial intelligence (AI) complement each other by harnessing the strengths of both human and machine capabilities. Citizen science generates terabytes of raw numerical, text, and image data, the analysis of which requires automated techniques to process in an efficient manner. Conversely, AI computer vision technology can require tens of thousands of images during the training process, and citizen science projects are well suited to provide large libraries of data. Herein, we describe how AI tools are being applied across the GLOBE Observer citizen science data ecosystem, where image recognition algorithms are supporting data ingest processes, protecting user privacy and improving data fidelity. GLOBE citizen science data has been used to develop automated data classification routines that enable information discovery of mosquito larvae and land cover labels. These advances position GLOBE citizen scientist data for discovery and use in environmental and health research, as well as by machine learning scientists working in the general field of GeoAI. |
| format | Article |
| id | doaj-art-df4574f9d8c94f61915afe0125a7d2d4 |
| institution | Kabale University |
| issn | 2057-4991 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Ubiquity Press |
| record_format | Article |
| series | Citizen Science: Theory and Practice |
| spelling | doaj-art-df4574f9d8c94f61915afe0125a7d2d42025-01-08T07:54:40ZengUbiquity PressCitizen Science: Theory and Practice2057-49912024-12-0191333310.5334/cstp.747729GLOBE Observer: A Case Study in Advancing Earth System Knowledge with AI-Powered Citizen SciencePeder V. Nelson0https://orcid.org/0000-0003-3979-9051Russanne Low1https://orcid.org/0000-0002-7912-4350Holli Kohl2https://orcid.org/0000-0001-8286-4221David Overoye3Di Yang4https://orcid.org/0000-0002-4010-6163Xiao Huang5https://orcid.org/0000-0002-4323-382XSriram Chellappan6https://orcid.org/0000-0002-5330-8549Farhat Binte Azam7https://orcid.org/0000-0002-0349-9703Ryan M. Carney8https://orcid.org/0000-0002-5537-5366Monika Falk9https://orcid.org/0009-0003-0963-5360Joan Garriga10https://orcid.org/0000-0002-4561-7835Larisa Schelkin11https://orcid.org/0009-0006-4654-6123Rebecca Boger12https://orcid.org/0000-0001-9628-8317Theresa Schwerin13https://orcid.org/0000-0003-1225-3251College of Earth, Ocean, and Atmospheric Sciences Oregon State University Corvalis, ORInstitute for Global Environmental Strategies, Arlington, VANASA Goddard Space Flight Center, Beltsville, MDAxient Corporation, Pasadena, CAWyoming Geographic Information Science Center, University of Wyoming Laramie, WYDepartment of Environmental Sciences, Emory University, Atlanta, GADepartment of Computer Science and Engineering, University of South Florida, Tampa, FLDept. of Computer Science and Engineering, University of South Florida, Tampa, FLDepartment of Integrative Biology, University of South Florida, Tampa, FLThe Blanes Center for Advanced Studies (CEAB), Higher Council of Scientific Investigations (CSIC), GironaThe Blanes Center for Advanced Studies (CEAB), Higher Council of Scientific Investigations (CSIC), GironaGlobal STEM Education Center, Inc., Boston, MADepartment of Earth and Environmental Sciences, Brooklyn College, Brooklyn, NYInstitute for Global Environmental Strategies, Arlington, VACitizen science and artificial intelligence (AI) complement each other by harnessing the strengths of both human and machine capabilities. Citizen science generates terabytes of raw numerical, text, and image data, the analysis of which requires automated techniques to process in an efficient manner. Conversely, AI computer vision technology can require tens of thousands of images during the training process, and citizen science projects are well suited to provide large libraries of data. Herein, we describe how AI tools are being applied across the GLOBE Observer citizen science data ecosystem, where image recognition algorithms are supporting data ingest processes, protecting user privacy and improving data fidelity. GLOBE citizen science data has been used to develop automated data classification routines that enable information discovery of mosquito larvae and land cover labels. These advances position GLOBE citizen scientist data for discovery and use in environmental and health research, as well as by machine learning scientists working in the general field of GeoAI.https://account.theoryandpractice.citizenscienceassociation.org/index.php/up-j-cstp/article/view/747computer visionartificial intelligencemosquitoescitizen scienceland coversmart phones |
| spellingShingle | Peder V. Nelson Russanne Low Holli Kohl David Overoye Di Yang Xiao Huang Sriram Chellappan Farhat Binte Azam Ryan M. Carney Monika Falk Joan Garriga Larisa Schelkin Rebecca Boger Theresa Schwerin GLOBE Observer: A Case Study in Advancing Earth System Knowledge with AI-Powered Citizen Science Citizen Science: Theory and Practice computer vision artificial intelligence mosquitoes citizen science land cover smart phones |
| title | GLOBE Observer: A Case Study in Advancing Earth System Knowledge with AI-Powered Citizen Science |
| title_full | GLOBE Observer: A Case Study in Advancing Earth System Knowledge with AI-Powered Citizen Science |
| title_fullStr | GLOBE Observer: A Case Study in Advancing Earth System Knowledge with AI-Powered Citizen Science |
| title_full_unstemmed | GLOBE Observer: A Case Study in Advancing Earth System Knowledge with AI-Powered Citizen Science |
| title_short | GLOBE Observer: A Case Study in Advancing Earth System Knowledge with AI-Powered Citizen Science |
| title_sort | globe observer a case study in advancing earth system knowledge with ai powered citizen science |
| topic | computer vision artificial intelligence mosquitoes citizen science land cover smart phones |
| url | https://account.theoryandpractice.citizenscienceassociation.org/index.php/up-j-cstp/article/view/747 |
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