Joint ICTP-IAEA Advanced School/Workshop on Machine Learning in Citizen Science

Citizen Science involves the public in scientific projects and can play an important role in generating large datasets. The convergence of data-driven Citizen Science projects and machine learning techniques can help tackle scientific and societal challenges. The lectures cover the following topics: Introduction to Citizen Science Introduction to Open Science Basic concepts/tools for Machine Learning techniques Challenges and opportunities of using Machine Learning in Citizen Science Ethical aspects of Machine Learning in Citizen Science Machine Learning for nuclear sciences and applications Using Machine Learning and Citizen Science to address the UN Sustainable Development Goals

Learning Data Naturally SLA (Special Libraries Association) 2021

Public participation in scientific research through citizen science is gaining popularity across the world. Through data collection, citizen scientists contribute to the creation of open and research-grade data and build data literacy skills. Academic librarians are often uniquely positioned to promote citizen science projects both in the classroom and among community advocates, connecting researchers with life-long learners for the benefit of open science. During the on-demand session and throughout the conference, participants and attendees will ‘naturally’ engage with the process of science and learn data literacy skills such as data collection and sharing, by contributing to this dataset. Participants in the session will also be encouraged to pose questions, analyze data, draw conclusions, and communicate findings by exploring the data collected by conference attendees from around the world. Sign up/log into iNaturalist and join the project.