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This seminar is part of a series to provide societies and their journals with information and resources to help their communities be more knowledgeable and prepared to share data (and software) in a way that is relevant and meaningful for each discipline. This is a 12-month series. Following the planned presentation, participants will have ~30 minutes of Q&A and discussion specific to society engagement to improve data sharing, credit, and transparency. Aligning Funder Policy with Support from Societies: Case Study with NIH and FASEB 4 June 2021, 10am ET (1400 UTC) Speakers: Susan Gregurick, PhD, Associate Director for Data Science, NIH, Director, Office of Data Science Strategy (ODSS) (bio) Frank Krause, Executive Director and CEO, Federation of American Societies for Experimental Biology (bio) Yvette Seger PhD, Director of Science Policy, Federation of American Societies for Experimental Biology (bio) Host and Moderator: Cindy Paska, Executive Director – Council of Scientific Society Presidents Description: This seminar features the new NIH Data Sharing policy (October 2020) and the developing collaboration with the Federation of American Societies for Experimental Biology (FASEB) support their societies and researchers in preparing for the policy implementation. FASEB, and their members societies, are working on awareness, education, and incentives to help researchers funded by NIH to be prepared to meet these new data sharing policy requirements. Seminar Recording: https://youtu.be/aNuZWrCKKnI
Special thank you to Laura Lyon of AGU and her support organizing and managing this seminar.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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