Human and Machine-Readable Justifications and Justified Decisions Based on 'YAML'
Export justification as YAML
Export a justifier specification to JSON
Concatenate two or more structured justifier objects
Producing a list of specifications
Easily parse a vector into a character value
Show your workspace contents
Wrap all elements in a vector
Concatenate to screen without spaces
Clean your workspace
Programmatically constructing justifier elements
Apply multiple DiagrammeR global graph attributes
Conversion between base10 and base30 & base36
Set your justifier workspace identifier
Flatten a justifier tree
Generate unique identifier(s)
Get your justifier workspace identifier
Get your justifier workspace identifier
Conditional returning of an object
Import a structured justifier object from JSON
Load Justifications from a file or multiple files
Document a decision
Merging to justifier specification lists
Options for the justifier package
Parsing justifications
Generate a random slug
Create a reference to one or more justifier objects
Repeat a string a number of times
Sanitize for DiagrammeR
Save your workspace
Leverages the 'yum' package to implement a 'YAML' ('YAML Ain't Markup Language', a human friendly standard for data serialization; see <https://yaml.org>) standard for documenting justifications, such as for decisions taken during the planning, execution and analysis of a study or during the development of a behavior change intervention as illustrated by Marques & Peters (2019) <doi:10.17605/osf.io/ndxha>. These justifications are both human- and machine-readable, facilitating efficient extraction and organisation.