- Schedule of Classes - June 25, 2020 7:14PM EDT
- Course Catalog - June 25, 2020 7:15PM EDT
Course information provided by the Courses of Study 2019-2020.
In an era that confronts us with an overwhelming capacity to collect data, knowing how to manage data is essential. Not only does the National Science Foundation (NSF) require a data management plan with all grant applications, growing numbers of funders and publishers have data sharing requirements. Data management is equally important for the individual researcher trying to document, organize and evaluate empirical information. In this course, we will discuss best practices for organizing data for efficient statistical and graphical analysis, developing science metadata, and sharing and archiving research data.
When Offered Spring (not offered every year).Outcomes
- Describe their research data lifecycle in order to identify areas for improvement in the research and data management process.
- Follow best practices involved in creating a flat database in order to maximize the likelihood of long-term preservation and potential for reuse.
- Follow best practices for documentation and recording of metadata to maximize the likelihood of effective long-term use and reuse by themselves or others.
- Interact with SQLite for analysis and visualization.
- Evaluate disciplinary data repositories in order to determine requirements and suitability for data deposit.
- Use the documentation accompanying a data set in order to evaluate data quality.
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