Open and FAIR Science: Data Sharing, e-Infrastructure, Data Citation and Reproducibility
Open Science is widely accepted as a new research paradigm to accelerate scientific innovation. It commonly refers to the top-down policies making results of publicly-funded research freely available and accessible. Open Science also refers to community-supported bottom-up approaches such as citizen science, crowdfunding, and interdisciplinary research. Other stakeholders (research institutions, funding agencies, scientific editors, etc) are also fostering open science using tools like data management plans, data citation and the use of persistent identifiers. All these approaches envision the transformation of research process to meet to the FAIR (Findable, Accessible, Interoperable, and Reusable) principles.
Following the past sessions at the JpGU and AGU Fall Meetings since 2018, this session reviews the current broad spectrum of Open Science in international contexts. The session welcomes a wide range of papers and posters covering (but not limited to) open research data, open source licenses, data papers and journals, data repository, e-infrastructures and platforms for sharing data, scientific cloud infrastructures, FAIR principles, Persistent Identifiers (PID), data management, citizen science, crowdsourcing, crowdfunding, transdisciplinary research, capacity building, international networking, and deployment in earth and planetary sciences.