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CRDDS Research Data Bootcamp

Research Data Bootcamp Overview

Welcome to the Research Data Bootcamp for incoming CU Boulder graduate students. The Bootcamp is sponsored and organized by the Center for Research Data and Digital Scholarship (CRDDS), which is a collaboration between CU Boulder University Libraries, and Research Computing. You can view the CRDDS website here.

As incoming graduate students, it is likely that you will work with research data at some point during the course of your respective programs. The goal of this Bootcamp is to provide you with an overview of some of the skills, strategies, and best practices that will help you to get started in pursuing this kind of work. The Bootcamp does not presuppose any prior experience in working with research data, and all of the sessions are introductory in nature. Our purpose is not to help you master any given topic, but to provide a useful and productive starting point for further exploration and learning. As you explore further after the Bootcamp and into the semester, we hope you’ll make use of CRDDS’s many resources, such as opportunities for individual consultations and workshops (many of which will cover the material introduced here in greater depth). More information about these opportunities is provided on the CRDDS website. For related offerings, please also see the website of our collaborators at the Laboratory for Interdisciplinary Statistical Analysis (LISA).

In thinking about the various skills and tasks that are relevant to projects that involve research data, librarians and data professionals often think in terms of a heuristic called the research data lifecycle:

Research Lifecycle

The lifecycle model specifies, in broad terms, the distinct yet interconnected stages of a data-intensive research project; each stage involves a variety of more specific tasks and competencies, as represented in the following graphic from the CRDDS website:

Research Lifecycle Tasks

By attending the Bootcamp, our hope is that you will be empowered to navigate the research data lifecycle with respect to your own work, in a deliberate and intentional way.

The different sessions of the Bootcamp address themselves to various stages of this research data lifecycle (italicized words correspond to the stage(s) of the research data lifecycle that the session will emphasize).

  • The first session, on Data Management will be taught by Adi Ranganath (Data Librarian at CRDDS) and Dylan Perkins (Director for Education and Training at CRDDS). It will explore basic principles of data management, and introduce tools for data management and storage. (Plan; Develop; Preserve)
  • Our second session, on Finding Data, will be taught by Liz Novosel (Subject Librarian at CU Boulder Libraries). It will provide you with an introduction to basic strategies for finding data that is relevant to your research needs. (Plan)
  • Our third session, on Qualitative and Humanities Data will be taught by Nickoal Eichmann-Kalwara (Digital Scholarship Librarian at CU Boulder Libraries). It will provide an overview of different data types, with a particular focus on tools and principles for working with qualitative data. (Plan; Develop; Publish; Preserve)
  • Our fourth session, on Ethics and the Social Context of Data, also taught by Nickoal Eichmann-Kalwara, explores basic principles of data ethics that you should consider when working with your research data. (Plan; Develop; Publish; Preserve)
  • The fifth session, on GitHub and GitHub Pages, will be taught by CU Boulder Libraries’ Map and Earth Sciences Librarian Phil White. It will explore how you can use GitHub and GitHub pages as platforms to collaborate with others, and to share and disseminate your work (Publish; Preserve)
  • The sixth session, on Data Publishing and CU Scholar, taught by CRDDS Scholarly Communication Librarian Melissa Cantrell, will discuss basic principles of scholarly communication as it relates to data research, and best practices for data archiving (Plan; Publish; Preserve)
  • The seventh session, on Data Analysis in R, will be taught by Adi Ranganath (data librarian at CRDDS). It aims to introduce R novices to useful principles, tools, and packages for data-based research in R/R Studio (Develop).
  • The eighth session, on Data Analysis in Python, will be taught by Tim Dunn (Visualization and Research Computing Specialist at CRDDS). It will introduce Python for data research. (Develop)

We will conclude the Bootcamp by discussing how you can continue your learning about the various topics introduced at the Bootcamp by participating in CRDDS programs and activities during the fall semester and beyond. We will also discuss the details of the Bootcamp microcredential, which you can earn by completing a small project that demonstrates your familiarity with the topics presented at the Bootcamp.