Data Literacy and Training


Data is a valuable asset. At UW–Madison, we use institutional data to make decisions that improve student experiences, increase operational effectiveness, and open the door to new discoveries. Applying good data management and literacy across the data lifecycle is critical for data to be trusted, appropriately shared, and ethically used.

These training modules were created for university staff, instructors, and student employees who handle and use the data that UW–Madison collects, stores, and maintains as part of our educational mission.

Training Modules

Introduction to the Data Lifecycle
In this module, you will identify the actions taken at different stages of the data lifecycle, building from the foundations of data management, data curation, and data literacy.

Data Literacy Track

Data Literacy Part 1: Finding and Evaluating Data
In Part 1 of the Data Literacy training module, you will gain an understanding of the UW–Madison institutional data landscape and identify critical skills needed to find, access, and evaluate data.
Data Literacy Part 2: Using data ethically
In Part 2 of the Data Literacy training module, you will gain skills in using data, including file organization, documentation, data transformations, data analysis techniques, and the ethics and responsibilities of conveying data.

Data Management Track

Data Management 101
This guide introduces key data management concepts and offers best practices when collecting data including how to store, assure, secure, and monitor data at UW–Madison.
Planning for Data Management
Before collecting or acquiring data, establish a plan for how the data will be managed throughout the lifecycle and consider how any laws, rules, and regulations may apply.
Five ways to document your data
How understandable will your data be to other users, including your future self? This guide considers five ways to document data, from just-getting-started to more complex tools.

Additional Data Training Resources

Key Terms

Institutional data is any information, regardless of medium, generated, collected, stored, maintained, transmitted, enhanced, or recorded by or for the university to conduct university business. Institutional data is owned by the university and considered a shared university resource. Read full definition in the Institutional Data Policy.

Examples of institutional data include:

  • Student records
  • Employee data
  • Financial and budgeting information
  • Teaching and learning data
  • Facilities and sustainability data

Research Data is any data generated by research conducted at the university, under the auspices of the university, or with university resources. Read the full definition in the Research Data Stewardship Policy

Examples of research data include:

  • Instrument readings
  • Survey results
  • Statistical and computational models and their output
  • Properties derived from physical samples
  • Software code

Tip: For more resources on how to manage Research Data generated by researchers and scholars, see the Researcher Toolkit and related policy on Data stewardship, Access and retention.

Contact Us

Feedback? Data related training missing from this list? Contact us at c/o Lisa Johnston, Director of Data Governance.

Cite as: UW–Madison Data Literacy and Training Modules, Office of Data Management and Analytics Services, University of Wisconsin–Madison.
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