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Use this guide to learn more about research data management, and find information about planning and managing your data throughout its lifecycle. Take note of the Quick Tips tab to learn 5 things that you can do now to better manage your data.
We recorded a webinar on April 14, 2022. Learn about five key practices for good management of your research data. View the slides and the recording below.
Most of the content on this page is adapted from the University Library System, University of Pittsburgh.
Graphics in this LibGuide are designed by Ashley Zeidler, MLIS, Medical College of Wisconsin.
Research data management (or RDM) is a term that describes the organization, storage, preservation, and sharing of data collected and used in a research project. It involves the everyday management of research data during the lifetime of a research project (for example, using consistent file naming conventions). It also involves decisions about how data will be preserved and shared after the project is completed (for example, depositing the data in a repository for long-term archiving and access).
There are a host of reasons why research data management is important:
At a broad level, data are items of recorded information considered collectively for reference or analysis.
Data can occur in a variety of formats that include, but are not limited to,
Data can be defined in a variety of ways, depending the discipline and the context. When it comes to making decisions about managing your research data, you may wish to consult the definitions used by your funder.
An important first step in managing your research data is planning. To get you started thinking about data management planning, here are some of the issues you need to consider:
For more insight into the questions you should ask and answer, check out Data Management Checklist (UK Data Archive) (PDF, page39)
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