Description:

One of the primary enablers for achieving Environmental Security is the smart and rational integration of environmental intelligence into all aspects of social, economic, political, and science-based decision making. The volume of relevant environmental data and information is growing rapidly, making the extraction of actionable environment intelligence more challenging by the minute. Effective science data stewardship can help ensure the basis of environmental intelligence, scientifically validated environmental data products and services, are efficiently generated, made easily discoverable and accessible and can be effectively integrated into the decision rubrics of our most pressing societal challenges.

Advances in emerging technologies such as Artificial Intelligence (AI), Machine Learning (ML), and nanotechnology offer great potential in improving the ability of organizations and individual practitioners to implement fully the tenants of science data stewardship across the entire data lifecycle. The intent of this session is to provide a forum for discussing data stewardship and management best practices for heterogeneous Earth and atmospheric science data. This session seeks submissions that highlight efforts to develop flexible data management plans; to more accurately describe data via metadata and data formats; to more consistently and thoroughly document data methods and quality; and to make data more openly accessible and discoverable. This session is designed to bring together science data stewardship developers and practitioners so that they can share their ideas, requirements, lessons learned and innovations as a step forward in the continuing evolution of the community of practice as it seeks to leverage several relevant emerging technologies.