Data management is the practice of collecting, organizing, and accessing data to support productivity, efficiency, and decision-making. Many researchers create and follow a Data Management Plan (DMP) which helps determine how the data is collected, documented, organized, stored, accessed, and disseminated. It is a controlled progression of how data is curated within and between each lifecycle stage of the data, from creation to completion of the project.
Fig 1. General Lifecycle of Data
The importance of data management grows as the amount of data produced and consumed continues to climb each year. Below are some reasons why data management is important.
Data management will...
Also, information becomes lost over time unless it is intentionally captured during the research process. By creating and following a data management plan, researchers walk through the process of considering different aspects about their data that they might not have considered. The following expandable diagram shows how information can be lost over time through information entropy.
Fig 2. Information Entropy
A data management plan (DMP) helps researchers work with, manage, share and archive their data effectively. A DMP typically describes what data will be produced; how each type of data will be organized, documented, standardized, stored, protected, archived, and shared; who will take responsibility for the various activities; and when these activities will take place over the course of the project.
When developing a DMP, the following are some questions to consider:
The California Digital Library has created a free, open-source resource called DMPTools to guide researchers through the process of creating a data management plan, whether as part of a funding requirement or for their own benefit. The brief video above describes the DMPtool.
DMPTool is an excellent place to start. This comprehensive, easy-to-use, open-source tool guides you through a developing a data management plan tailored to your needs that you can easily export. You'll create an ID and password, so your plan will stay private. Step by step instructions let you target your plan for a particular granting body. You can also browse an index page with sample plans, templates, and guidance.
This Primer on Data Management [PDF] from DataOne covers the basics of data management, best practices, and how to consider data management in the larger scheme of your research.
If you have questions about creating a data management plan, please contact, John Repplinger (jrepplin@willamette.edu).
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Many online resources exist with sample data management plans, some of which are from actual successful proposals. Take a look at the examples below to get a better understanding of what a DMP should include.
