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FR notice: https://www.federalregister.gov/documents/2020/06/15/2020-12855/leveraging-existing-bioenergy-data-workshop
 
The Department of Energy (DOE) is announcing an online public workshop entitled, “Leveraging Existing Bioenergy Data Workshop.” The Bioenergy Technologies Office (BETO) seeks to discuss how to collect and valorize underused datasets and associated knowledge, with the future goal of making this information public on existing databases.

The workshop will be held online on July 21, 2020, 12:30 p.m.—5:00 p.m. EDT, July 22, 2020, 10:00 a.m.—5:00 p.m. EDT, and July 23, 2020 12:30 p.m.—5:00 p.m. EDT. To attend the workshop, you must register by July 14, 2020.

BETO seeks to gather input on how to collect and valorize underused datasets and associated knowledge, with the goal of making this information public on existing databases. This workshop seeks to connect industry scientists, data owners, and lawyers with federal government, academic, and national laboratory representatives to shepherd valuable datasets and other knowledge to be used to maximum benefit. This effort would bolster the growing bioeconomy with industrially-relevant data across the supply chain, and result in accelerated development and utilization of biotechnologies. BETO intends to cover the following topics at the workshop: Existing Data Quantity/Quality; Data Monetization & Valuation; and Data Acquisition
 
Members of the public are welcome to register and attend the workshop. To attend the workshop, register online through the workshop web page at https://www.energy.gov/​eere/​bioenergy/​events/​leveraging-existing-bioenergy-data-workshop by July 14, 2020.  
 
Workshop attendees will have the opportunity to speak for up to five minutes and share up to three slides relevant to the workshop topic. Attendees interested in presenting should email their slides to Dr. Elizabeth Burrows at Elizabeth.Burrows@ee.doe.gov by July 6, 2020. Submission does not guarantee a live presentation spot. Participation is subject to available time and topic relevancy.

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