When:March 24, 2021, 1-3 p.m. ET
Where:Virtual (connection information will be provided after registration)
Who Should Attend:
Data producers, especially early career scientists, and those who would like to make data management easier and improve the usability of their data.
About This Workshop:
Scientists spend considerable time collecting and analyzing data, and writing research papers, but an often-over looked activity is effectively managing the resulting data. The purpose of this workshop is to use real-world NACP and related data as examples to provide guidance on fundamental data management practices that invesitgators should perform to improve the quality of their datasets and also on how to submit and publish their datasets at the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC). The target audience is early career scientists (post-docs, graduate students), but is open to any researchers who would benefit from developing better data management skills. Faculty members who would like to include exercises on best practices for preparing data as part of their curricula are encouraged to attend. Topics covered will include data structure, quality control, data standardization, and data documentation. We will also discuss the elements of an effective data management plan for use in grant proposals and project planning. By following the practices taught in this workshop, your data will less prone to error, more efficiently structured for analysis, and more findable, accessible, interoperable, and reusable (FAIR).
- Benefits of Manging Data Well for Sharing and Publishing
Introduction to the benefits of proper data management and publicaiton, including open and reproducible research; increased data discoverability, accessibility, and usability; and credits toward your professional profile through dataset citation.
- Best Practices of Data Management
Overview of data management planning and practices that will help successfully organize, preserve, and share data.
- Data Quality Assurance
How to perform basic quality assurance checks on common data file formats (e.g., CSV, GeoTIFF, and netCDF) to provide dataset interoperability and reusability.
- Submitting Data to the ORNL DAAC
Description of the dataset submission process and summary of information that should accompany data files to increase usability
- Question & Answer Session