About this course
Welcome to “Analyzing Your Documents!” In this course, you’ll learn how to analyze and evaluate your documents—a key step in the editorial process. You might think that you’re already intimately familiar with your documents inside and out. And perhaps you are. But how well do you know them beyond your own perspective? Before publishing them, it’s crucial to think about your documents in a specific progression—first as individual units, then as an entire edition. A careful analysis of documents can lead to more nuanced editorial methods, a well-thought-out selection policy, and complementary technology solutions. A thorough analysis can also improve your project workflow and increase accessibility to your completed edition. Ultimately, analyzing your documents is an essential early step in the process of creating and publishing an edition.
What you'll learn
- to list different categories of document types and their characteristics.
- to describe differences in document types.
- to explain how the form and function of a document affects its presentation.
- to engage in basic-level document analysis.
- to explain why analyzing documents is essential in the editorial decision-making process.
Course Content
Guides
Contributors
Supervision
- Krista Tomaselli
Visualization
- Katie Blizzard
- Krista Tomaselli
Writing—Review & Editing
- Neel Agrawal
- Katie Blizzard
- Cathy Moran Hajo
- Emily Middleton
- Russ Sprinkle
- Serenity Sutherland
- Krista Tomaselli
Course Glossary
- Annotation
The use of descriptive, contextual, referential, or illustrative content or structure that supports the discoverability and accessibility of source materials. Annotation may take many forms (footnotes, source notes, metadata, glossaries, essays, indexes, keywords, images, maps, and more) and multiple forms of annotation may be used by a project.
- Metadata
Essentially, data about data. It can be used to describe the content, physical or structural features, and/or administrative elements of data. In providing such descriptions, metadata supports the management and discoverability of data. See the University of North Carolina Library's definition of metadata for more information: https://guides.lib.unc.edu/metadata/definition.