Quality data are timeless and depend on detailed and enduring description and clear presentation to support findings, further study and downstream application. However, in the course of research, scientists often focus more on interpretation of the experiment at hand and less on managing individual data values and files. Can you unambiguously interpret your data from your notes last year? How do you know if the data you are analyzing are accurate and complete? What happens if data are lost due to technical failures, misfiling, or the original collector moves on?<br/><br/>Robust data management and notetaking practices are highly critical, highly contextual and highly personal for successful research. Cornell University has taken a responsive approach to research data support through a network of campus consultants with diverse expertise and backgrounds that address data management throughout the research life cycle. This talk will highlight some of the programs and services offered and lessons learned by this team that have intersected with the needs of chemical researchers managing their data.

Don't trust your future self": Wholistic data practices one conversation at a time at Cornell University

Macromolecular Chemistry: The Second Century

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ACS Spring 2020 National Meeting & Expo

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.