This guide lays out practical considerations and information to aid you in managing your research throughout its' life cycle, including the steps you will take to collect, safeguard, archive, and make available the data used for the research in question.
Many key granting organizations, like NSF, NIH, NEH and more, now require submitters to include a Data Management Plan as part of their application. These plans outline the best practices in data management that you will apply throughout the course of your grant. You can see some more background on this issue, or get started by selecting a tab at the left of the page.
Research data is any information that has been collected, observed, generated or created to validate original research findings.
Although usually digital, research data also includes non-digital formats such as laboratory notebooks and diaries.
Research data can take many forms. It might be:
Research data can be generated for different purposes and through different processes.
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: