Data Collection & Management (LAS 6292)

Graduate Course, 3 credits, Spring Semester

Course Objectives

This course is for graduate students from any discipline – social sciences, humanities, biophysical sciences – and at all stages of their graduate program. It is an introduction to methods for collecting, organizing, managing, and visualizing both qualitative and quantitative data. Students will gain hands-on experience with best practices and tools; at the conclusion of this course students will be able to:

  • Describe the different types of research data;
  • Explain the need for and benefits of data management and sharing;
  • Describe and implement best practices for the collection, storage, management, archiving, and sharing of research 1. data;
  • Find, download, and analyze publicly available data from repositories;
  • Carry out simple and reproducible data corrections and dataset organization;
  • Describe public policies and agency requirements for data management and sharing;
  • Articulate the major legal and ethical considerations regarding the collection, use, and storage of research data 1. (e.g., privacy/human subjects, intellectual property);
  • Create and Implement and a Data Management Plan;
  • Identify and properly use tools and techniques for more efficient and secure data collection in the field.

FAQs

There are no prerequisites other than graduate student standing

YES! I assume you have no prior experience with programming.

This course was created for students in the TCD and MALAS program, whose multidisciplinary projects often require collecting a combination of quantitative and qualitative data. It is appropriate for students from all fields: biophysical sciences, social sciences, humanities, education, journalism, etc.

This course is in the TCD Methods category, so PhD students earning the TCD concentration can count this course towards their contration requirements.

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