Committed to supporting rigorous, transparent and reproducible research at VCU through the promotion and development of practices and tools that facilitate modern data science.
Data Science is both the science and the art of working with data, encompassing every step that exists between asking a question and answering it. Regardless of your field, the process of extracting information from data entails a common set of challenges including:
- storage, retrieval and tracking of data
- cleaning and reformatting raw data into a format suitable for exploration and analysis
- executing transformations and manipulations
- producing meaningful analyses and illuminating visualizations
Formal training in many of these tasks is rare, leading to a propagation of suboptimal solutions that can impede the scientific process. Whether you're an avid analyst or someone who occasionally uses Excel to make bar graphs, investing time in developing basic data science skills and adopting modern data analysis workflows will improve the efficiency of analyses, produce easily verifiable results and facilitate collaboration.
Resources and tools we recommend.
We offer courses and workshops to learn about practical techniques and tools for improving skills in scientific computing.
- » 7/25 - Managing Research with the Open Science Framework
The Open Science Framework (OSF) is a free, open source application built to help researchers manage their projects and workflows. The OSF is part collaboration tool, part version control software, and part data archive. This workshop will provide an overview of the OSF and demonstrate how VCU researchers can use it for securely storing data and materials, organizing projects, coordinating with collaborators and making all or part of your work public and citable.
- » Reproducible Data Analysis with R
- » Managing Research with git and GitHub
If you have any comments or questions about the Data Science Lab please email us at email@example.com.