Data Management and Reproducibility

Workshop Description

Computational tools make it easier than ever to collect, analyze, and share data and results in transparent and reproducible ways. To achieve reproducibility, it is important to set systems in place and manage data thoroughly. Data management is the process of handling, organizing, documenting, and preserving data used in a project/research. It helps your research outcomes be transparent, maximizing your work’s practical use and value. This lesson provides an overview of all the meaningful steps in a research project and dives into how to plan for successful data management. We will also discuss tools and systems to help you organize and document your work for better reproducibility and to facilitate collaboration (including with yourself).

Learning Objectives

  • Recognize common data management challenges in synthesis and collaborative research.
  • Apply best practices for organizing, documenting, and harmonizing ecological datasets.
  • Develop a reproducible data workflow from data discovery to publication.
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Resources