Research Data Management is the collection, organization, documentation, and storage of research data. It can be boiled down to the "Who, what, when, where, and how" of data that is used for research.
In 2016, the ‘FAIR Guiding Principles for scientific data management and stewardship’ were released. The authors intended to provide guidelines to improve the Findability, Accessibility, Interoperability, and Reuse of digital assets. The principles emphasize machine-actionability (i.e., the capacity of computational systems to find, access, interoperate, and reuse data with none or minimal human intervention) because humans increasingly rely on computational support to deal with data as a result of the increase in volume, complexity, and creation speed of data.
There are many different aspects to Research Data management, but here are a few of the basics. If you have any questions, don't hesitate to get in touch!
Back Up Your Data!
After the Research is Over
A Data Management Plan describes your data files, your plans for data storage, and rules for sharing your data. Many granting agencies now require them as a part of research proposals.