Data Management: Home

If you're looking for quick solutions to common data management challenges, try these:

DDI version 3.0 Combined Life Cycle Model

• Data Management Plans are also referred to as DMPs. In this tab, learn about the requirements for data management plans for various funding agencies, templates for DMPs, and find other resources to help you manage your research data.
• Organization and Format - Understand the various ways you can strategically organize and arrange data and information into a digestible, user friendly format, and learn why preservation is important for your data. Click to the sub-page to learn about metadata, what it is, and why it is important to your research. 
• Sharing and Storage - Discover why the experts believe you should share your data, the methods for sharing, publication practices, and the different ways and places you can store your data.  
• The Glossary helps define some of the terms used in this guide.
• IP and Copyright details how intellectual property and copyright are treated with respect to data.
• Blogs & More has additional tools to help you stay informed of the changing data management landscape and utilize best practices.

Data management encompasses the processes surrounding collecting, organizing, describing, sharing, and preserving data.

Why is data management important?

The most effective and efficient data management practices begin at the research planning stage. With early planning for data management you can:

• Save time by having a plan in place for your data from the beginning of your project.
• Comply with legal and funder requirements.
• Increase the visibility and impact of your research by making your data searchable and citable.
• Support open access and foster new research by preserving your data and making it accessible to other researchers.

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