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The Data Foundation invites Data Coalition Members to please join us on Tuesday, June 9, 1:00 - 2:00 pm ET for a virtual members-only roundtable, "Paths Forward for Integrative Climate, Nature, and Economic Reporting" with Ken Bagstad, Data Foundation Climate Data Collaborative Senior Fellow. Bagstad will be speaking at 2026 Data Summit, whether or not you're able to attend the Summit, this will be a great opportunity to meet and hear from one of the Climate Data Collaborative’s fellows!
While demand for reliable nature data to inform economic, planning, and land use decisions has never been greater, today’s underlying, fragmented data systems fail to meet decision makers' needs. In this talk, Ken Bagstad will describe some of the barriers to more seamlessly aligning nature, climate, and economic data, including semantic heterogeneity of data and inconsistent descriptions of fit-for-purpose that limit the proper reuse of data. Opportunities exist to address those barriers, including through careful application of AI tools. Doing so can help to move nature data toward investor-grade quality: data consistent and auditable enough to support financial risk assessment, capital allocation, policy evaluation, and credible disclosure at scale.
Ken Bagstad is a Senior Fellow at the Data Foundation's Climate Data Collaborative. He has led efforts in the U.S. and globally to design and implement standard practices for natural capital accounting and environmental-economic statistics, putting the economic value provided by nature on balance sheets for governments and businesses. His career includes 14 years at the U.S. Geological Survey, where he coordinated efforts spanning 27 Federal agencies and over 100 technical staff to develop and report on the diverse contributions of ecosystems and natural resources to the U.S. economy. Bagstad has served as a senior technical advisor for international organizations including the World Bank and the United Nations. His work also focuses on semantic interoperability for environmental and economic data and models, which offer improved transparency, replicability, and timeliness for computational workflows, in particular through a long-standing collaboration on the Artificial Intelligence for Environment and Sustainability (ARIES) Project. He holds a Ph.D. in natural resources and ecological economics from the University of Vermont.
