LAS 6292: Data Collection & Management

This course is designed 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 for:

  • Minimizing errors in data collection and transcription
  • Entering and organizing data in ways that will streamline analyses
  • Working with publicly available data
  • Data storage and archiving
  • Legal and ethical issues related to data collection and use.
  • Current issues surrounding privacy and human subjects

All students will work with real data sets (ideally their own) and prepare a data collection and management plan for their own research projects.

Course Schedule

Week Date Topic
1 1/7 Data across disciplines, Research Data Lifecycle
2 1/14 File Formats, Naming conventions, Storage, and Security
3 1/21 Data structure and formatting I
4 1/28 Data structure and formatting II
5 2/4 Metadata & Documentation
6 2/11 Efficient Data collection
7 2/18 Data entry, QAQC
8 2/25 Version control, Introduction to Reproducibility
10 3/11 Data processing & visualization I
11 3/19 Data processing & visualization II
12 3/18 Legal and Ethical Issues
13 3/25 Data Sharing, Reuse, and Citation
14 4/1 Data repositories and archiving
15 4/8 Data Management Plans
16 4/15 Tools for Project Management and Collaboration
17 4/22 Free day to work on Individual Projects
Finals Week 5/2 Project Submission no later than 5/2 @ noon