How Does Good Research Data Management Practice Support Research Repeatability

Research Repeatability

An integral requirement of academic research data management (RDM) is ensuring research repeatability to preserve the continuation of scientific integrity. Repeatability allows other researchers to validate findings, build on existing work, and maintain high-quality standards and public trust in research outcomes.

Well-document data and metadata significantly improve reuse

Effective RDM practices, such as thorough data management plans, organizing data systematically, storing data in accessible formats, and managing and controlling access to research data, facilitate the process of discovery and create a clear roadmap for others to follow. For instance, a study by Wallis et al. (2013) highlights that well-documented data and metadata significantly improve the likelihood of successful data reuse. When researchers provide detailed descriptions of their data collection processes, analysis techniques, and tools used in their research, it clarifies their procedures and allows others to accurately evaluate academic publications. This can also expedite the peer review process and enhance its accuracy, enabling more research to be published faster without compromising quality standards.

Guarantee long-term accessibility

Furthermore, storing data in trusted repositories guarantees long-term accessibility, which is crucial for ensuring that studies can be repeated effectively. According to a report by the National Academies of Sciences, Engineering, and Medicine (2019), transparent data sharing not only supports reproducibility but also creates an environment of innovative collaboration. By adequately adopting RDM best practices and solutions that are designed to enable them, researchers are able to contribute towards a culture of accountability, which ultimately strengthens the credibility of the scientific community.

The FAIR Principles

In conclusion, good RDM is not just about preserving data, it is about defending the future of academic research itself. By enabling researchers to easily embrace strong research data management practices, myLaminin ensures that your data is not only secure but also accessible for future scholars. myLaminin's commitment to FAIR (Findable, Accessible, Interoperable, and Reusable) science principles, and reliability in our data security, team collaboration, agreements management, data collection, integrated Research Ethics Board, and audit trail capabilities supports ongoing discovery and innovation, helping us all build a more informed future.

References:  

Wallis, J. C., Rolando, E., & Borgman, C. L. (2013). If we share data, will anyone use them? Data sharing and reuse in the long tail of science and technology. 

National Academies of Sciences, Engineering, and Medicine. (2019). Reproducibility and Replicability in Science. National Academies Press.

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Quenifer Lung (article author) is a Western University Honours Business & Globalization student and myLaminin intern as part of the University's WMA program.