Best Practices in Scientific Data Management
- Responsible Conduct of Research
Are you in the midst of designing a research study that will require you to collect a lot of data? Are you thinking about working with a vendor to store or process your research data securely? Have you completed a research study and are trying to get your work published in a journal that has data-sharing requirements?
The ability to generate large amounts of scientific data and combine data from multiple sources continues to increase rapidly. All scientists should have the skills to handle large volumes of complex data and utilize data sets in ways that respect intellectual property and privacy concerns.
Learn best practices in data management, strategies, tools, and techniques needed to securely manage your research data throughout a project, and how to comply with funder and journal requirements for data sharing.
About the Speakers
Ariel Deardorff is a data services librarian and member of the library’s data science team at UC San Franciso (UCSF). She teaches classes and does research on data management, open pedagogy, and reproducibility in the health sciences. She has a Master’s degree from the University of British Columbia and was a fellow with the NIH before starting at UCSF.
Scott Pegg is the chief information officer at the Gladstone Institutes.
Gladstone Institute’s Office of Postdoctoral and Graduate Affairs
The Responsible Conduct of Research program provides Gladstone’s scientific community opportunities to openly discuss ethical issues in scientific research and complete the requirements of the NIH policy. Courses are held every 2 months and cover a variety of topics on scientific ethics.