Foundational Practices of Research Data Management

Kristin Briney,Heather Coates,Abigail Goben

doi:10.3897/rio.6.e56508

Abstract

The importance of research data has grown as researchers across disciplines seek to ensure reproducibility, facilitate data reuse, and acknowledge data as a valuable scholarly commodity. Researchers are under increasing pressure to share their data for validation and reuse. Adopting good data management practices allows researchers to efficiently locate their data, understand it, and use it throughout all of the stages of a project and in the future. Additionally, good data management can streamline data analysis, visualization, and reporting, thus making publication less stressful and time-consuming. By implementing foundational practices of data management, researchers set themselves up for success by formalizing processes and reducing common errors in data handling, which can free up more time for research. This paper provides an introduction to best practices for managing all types of data.

Highlights

The practices described in this article are foundational and broadly applicable, though projects may benefit from advanced data management practices and disciplinespecific standards, not addressed here, that are tailored to the needs of individual projects
Data management is the sum of a number of small practices that add up to being able to find and use data when you need it
Data management is most effective when these practices are habitual — consistent routines performed without extra effort

Summary

Introduction

Many of these practices extend or build upon project management techniques This is because, in order for scientific teams to collaborate effectively, they need to establish a shared understanding of a project’s tasks, including procedures for data management, and how the team will function. For this reason, good data management practices include behavioral changes and clearly identified roles and responsibilities. This article provides ten foundational practices to improve the management of research data and files across all disciplines. While not exhaustive, this is a guide to adding small routine practices to research workflows that provide maximum impact. Different groups of files can have different naming conventions, though do be sure to document each of them

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Conclusion