Research Data Management

Good research starts with good data. This guide will help you understand how to organize, store, protect, and share your data throughout your research journey. Whether you're a student or a seasoned researcher, mastering Research Data Management (RDM) makes your work more efficient, credible, and reusable.

The Research Data Lifecycle describes the stages that research data go through from the beginning to the end of a research project (Hodge, 2000). It typically includes planning, collecting, processing, analyzing, preserving, sharing, and reusing data. Understanding this cycle helps researchers manage their data effectively, ensuring it remains accurate, secure, and accessible throughout and after the project.

References:

Hodge, G. M. (2000). Best Practices for Digital Archiving: An Information Life Cycle Approach. D-Lib Magazine, 6(1).

        https://doi.org/10.1045/january2000-hodge

Want your research to have a bigger impact? The FAIR principles —Findable, Accessible, Interoperable, and Reusable—help ensure your data can be discovered, understood, and reused by others (Wilkinson et al., 2016). This guide will show you simple steps to make your data FAIR and future-ready.

See the original document for more details. 

Reference:

Wilkinson, M. D., Dumontier, M., Aalbersberg, Ij. J., Appleton, G., Axton, M., Baak, A., Blomberg, N., Boiten, J.-W., da Silva Santos, L. B., Bourne, 

        P. E., Bouwman, J., Brookes, A. J., Clark, T., Crosas, M., Dillo, I., Dumon, O., Edmunds, S., Evelo, C. T., Finkers, R., … Mons, B. (2016). The

        FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3(1), Article 160018.

        https://doi.org/10.1038/sdata.2016.18