The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

Creating Data Dictionaries

What is a Data Dictionary?

A data dictionary is a document that describes all variables in your dataset. It serves as essential documentation for:

Using the Shiny App

The easiest way to create a data dictionary is through the psychds Shiny app:

library(psychds)
run_psych_ds_app()

Navigate to “Update Dictionary” in the sidebar.

Step-by-Step Process

  1. Load your dataset - Select a Psych-DS dataset folder
  2. Edit each variable - Add descriptions, types, and constraints
  3. Define categorical values - Document allowed values and their meanings
  4. Set missing value codes - Define how missing data is coded
  5. Generate the dictionary - Save into metadata or export as HTML

See the Shiny App Guide for detailed instructions.

Output Formats

HTML (Default)

The HTML output features:

To save as PDF, open the HTML file in a browser and press Ctrl+P (or Cmd+P on Mac).

Best Practices

Writing Good Descriptions

❌ Bad: “age” ✅ Good: “Participant age in years at the time of initial assessment”

❌ Bad: “rt” ✅ Good: “Mean response time in milliseconds across all correct trials in the Stroop task”

Choosing Data Types

Use When
string Text, IDs, categorical values
integer Whole numbers (counts, ages)
number Decimals (measurements, proportions)
boolean True/false values
date Dates (ISO 8601 format)
datetime Timestamps

Documenting Categorical Variables

Always define what each category means, even if it seems obvious:

Value Label Description
1 Strongly Disagree Likert rating indicating strong disagreement
2 Disagree Likert rating indicating disagreement
3 Neutral Likert rating indicating neutral response
4 Agree Likert rating indicating strong agreement
5 Strongly Agree Likert rating indicating strong agreement

Missing Values

Document all codes that represent missing data:

Code Common Meaning
NA Not Available (R default)
N/A Not Applicable
-999 Common numeric missing code
. SAS/Stata missing
"" Empty string
-1 Sometimes used for “not asked”

Integration with Psych-DS

The data dictionary complements the dataset_description.json metadata. While dataset_description.json contains machine-readable metadata, the data dictionary provides human-readable documentation.

Both should be included in your Psych-DS dataset:

my_dataset/
├── dataset_description.json    # Machine-readable
├── data_dictionary.html        # Human-readable
├── README.md
└── data/
    └── study-exp1_data.csv

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.