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 on 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 and by The Chicago School.
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:
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)
This guide is based on the Research Data Management @ Pitt Guide by the University of Pittsburgh Library System. Additional content was adapted from the University of Connecticut Library from their Research Data Management Guide. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)