GEO OSE Track 1: Forging Cross-Stakeholder Partnerships to Accelerate Geoscience Discoveries: Cultivating Sustainable Disciplinary Open Science Communities

Investment in research is maximized when data are as open as possible: findable, interoperable, accessible, and reusable (FAIR). However, simply making data public in generalized repositories does not mean it is FAIR. Discipline-specific archiving will lower the barrier for scientists to make their data FAIR. The target disciplines of hydrology, oceans, and seismology were chosen because of their substantial but disparate existing resources and their demonstrated receptiveness to open data practices. The goal of this project is to build coalitions in three scientific disciplines by engaging stakeholders including researchers, publishers and data managers at multiple workshops and training events. They will develop community-vetted, disciplinary-specific data sharing frameworks; a web platform to implement the framework; and disciplinary leaders and liaisons to sustain the framework. The framework of community practices will also be captured to inform future use in other disciplines. The proposed work will build a sustainable community resource for three target disciplines to drive their community toward a shared vision of common data resources including digital objects, methods and tools that are grounded in Open Science and findable, interoperable, accessible, and reusable (FAIR) data principles. The process of developing discipline-specific frameworks will coalesce existing community resources and help to identify areas for development of leading practices, vocabularies, and integration of standards. The vetting process includes open science practitioners providing a steady influence on the long-term value of data as an asset and the overall need for better data management, preservation methods and protocols. Each discipline’s leadership, through adoption and awareness efforts, help shape the path that will benefit broader science goals: 1) Community resources identified in partnership with respective members; 2) Interoperable data that are machine-actionable supporting discovery, trust, and reuse; 3) discipline-specific leadership that intentionally fosters skills development in data management, Open Science, and FAIR data. Framework dissemination and socialization via disciplinary communities and meetings will lower key barriers to the realization of the value of Open Science practices by putting community-vetted resources where researchers share their research and connect to their colleagues. 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.