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SoTL Data Management and Documentation

Effective data management is essential to your SoTL project’s organization, reproducibility, and meaningful dissemination of findings. This collection provides guidance and practical tools for organizing your data, creating documentation, and avoiding common pitfalls.

Scholarship of Teaching
Updated December 2025
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Jess Taggart
Assistant Director & Assistant Professor
Office of the Executive Vice President and Provost
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01

File Management Best Practices

University of Virginia Library

This University of Virginia Library guide covers research data management best practices for any discipline, including project and file organization, file naming conventions, file types and formats, and version control.

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Jess Taggart

Managing research data is not necessarily the most exciting part of the research process, but it is one of the most important! This LibGuide provides a quick and practical way to save yourself future headaches.

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02

Metadata and Documentation

University of Virginia Library

This University of Virginia Library guide explains metadata and documentation for research data, covering README files, codebooks and data dictionaries, metadata, and controlled vocabularies.

Headshot of Jess Taggart
Jess Taggart

Creating careful documentation for your SoTL project may seem like an unnecessary part of the research process, but it is essential. Without it, you lose context for your project, which can set back your dissemination efforts.

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03

SoTL Journal Template

Jessica Taggart

This journal template, developed for the University of Virginia’s SoTL Scholars program, provides a clear structure to keep track of the details of your SoTL project.

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Jess Taggart

If you are looking for a ready-to-use template to document the details of your SoTL project, this journal is for you! It will help you organize your thoughts and process so that you never have to wonder, where did I get that instrument from? Where did I store that file? Why did I code the data that way?

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04

What Could Possibly Go Wrong? The Impact of Poor Data Management

Chris Eaker

This chapter examines consequences of poor data management. The author discusses common pitfalls and provides practical recommendations for avoiding these problems.

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Jess Taggart

You could likely come up with many poor outcomes of poor data management on your own; I appreciate that this article not only shares examples, but also highlights what could be done differently to avoid those issues in the first place.

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A Tibetan monk lost his life’s work after posing for a photograph with London Mayor Boris Johnson. A long-time Flickr user lost thousands of original digital photographs when the photo sharing service erroneously deleted them. The programmers of the movie Toy Story 2 nearly lost the entire movie file when someone accidentally typed a wrong command. A data set containing mistakes from careless data entry forced a scientist to request retraction of seven articles. What do these unfortunate situations all have in common? These are all situations in which poor data management practices caused problems that could have been avoided.

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05

Past Workshop Materials from Research Data Services

University of Virginia Research Data Services

This website links out to UVA Research Data Services’ workshop resources on a wide range of topics of interest, including data management.

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Jess Taggart

These workshop resources span a range of data management considerations relevant to SoTL scholars, from data storage best practices and creating a data management plan to choosing between data sharing repositories. I find these are skills not often taught to SoTL scholars - use these resources to learn from the experts!

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