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Twenty-first century research is enabled by the availability of vast amounts of data, collected across a wide range of temporal and spatial scales, often in real time. Entire fleets of satellites, drones and other devices monitor the Earth at ever-increasing resolution, adding to the enormous corpus of maps and metadata that enable sciences from geology to biodiversity. While citizen science - or crowdsourcing science - has been successfully leveraged over the past several decades to close the analysis gap arising from large amounts of data, the sheer scale and complexity of these new data sets presents new challenges. This project addresses these challenges through novel Citizen Science Cyberinfrastructure (CSCI) where new tools and techniques, including teaming humans with Artificial Intelligence (AI), are being developed to enable researchers to efficiently extract the best results from large and complex data sets. This effort incorporates mapping, machine learning, and data sharing innovations in biodiversity, geoscience, and astronomy research and expands the capacity of research communities across a wide range of disciplines to use citizen science as a suitable, open and sustainable research methodology. This project leverages NSF-supported cyberinfrastructure, including the Zooniverse citizen science platform with its nearly three million volunteers, to provide a novel cyberinfrastructure by: (1) integrating mapping infrastructure into Zooniverse to accelerate accurate processing and curation of often complex data sets for geoscience and biodiversity projects; (2) providing an "incubator" hub for researchers and developers to design and deploy innovative citizen science projects with a fast production turn-around particularly for AI training; and (3) providing cyber-pathways to existing cyberinfrastructure, creating documentation for Zooniverse projects to responsibly deposit their data into appropriate repositories, and facilitating workshops for Zooniverse project teams to develop best practices for data and model sharing. To ensure wide dissemination of the new CSCI, a strong Community of Practice is engaged and supported throughout the project effort. The project is led by the University of Minnesota in collaboration with the Adler Planetarium and the University of Oxford, as core Zooniverse institutions and astrophysics expertise, and joined by the University of Florida and the Florida Museum of Natural History with expertise in biodiversity, museum specimen collections, and data repositories, as well as Northern Arizona University with expertise in Earth Sciences, mapping cyberinfrastructure, and the study of the Antarctica’s Dry Valleys. As the largest citizen science platform, and with key tools for human-in-the-loop data analysis tasks, the Zooniverse is uniquely positioned to develop skills and best practices to lower the barrier for research teams to responsibly share data and models. This is carried out through fact-finding and demonstration with several key groups who are exemplars in the data and model sharing ecosystem, including GitHub, the National Science Data Fabric (NSDF), the Global Biodiversity Information Facility (GBIF), and Open Science Chain. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Up to $2.1M
2029-09-30
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