Data Management in Research: A Comprehensive Guide

Research Data Management (RDM) is a term that describes the organization, storage, preservation, and sharing of data collected and used in a research project. Learn more about RDM here.

Data Management in Research: A Comprehensive Guide

Research data management (RDM) is a term that describes the organization, storage, preservation, and sharing of data collected and used in a research project. It involves the daily management of research data throughout the life of a research project, such as using consistent file naming conventions. The research data lifecycle involves the movement of data from creation to preservation and reuse, to infinity. Astronomers, for example, have been doing this for decades by calibrating their observations and archiving huge amounts of telescopic survey data in standardized machine-readable catalogs for reuse.

Universities should define expectations through an RDM policy, and support staff will provide the services. Scientists whose thesis could be based on a limited number of field observations may need to archive only a small amount of data. Journal publishers are increasingly demanding that researchers make available to researchers all the data underlying the findings described in their manuscript at the time of publication. Managing data well and adhering to policies and frameworks can increase debate and the potential for new queries in your field.

How research data is handled depends on the type of data involved, how that data is created or collected, and how the data will be used now and in the future. This should help ensure that you continue to receive funding and open up to innovation and potential new uses of data. Although usually digital, research data also includes non-digital formats, such as laboratory notebooks and sketchbooks. Scientists who are unsure of the metadata requirements or protocols they should use for their data correctly should contact the library services of their host institute.

Using a DOI helps that data can be cited, traced and found, so that research data, as well as publications based on that data, can form an alternative but important part of a researcher's output. File naming and folder structure conventions should be made early in the project. Metadata includes descriptions such as in the code or tags of the file itself.