Splunk® Style Guide

Splunk Style Guide

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Write unbiased documentation

Splunk documentation serves a global audience, so it's essential that the documentation reflects the full scope of the Splunk community. Know that words have meanings beyond their dictionary definitions, and strive to write unbiased documentation that considers the experiences of everyone.

Keep the following points in mind when writing about Splunk products to make sure the docs are inclusive:

  • Write in plain language. Metaphors and idioms aren't always understood internationally and can be offensive to some cultures. Read more in Use plain language.
  • Use gender-fair wording and neutral pronouns in your writing. Read more in Gender-neutral pronouns.
  • Choose diverse names and genders when you create use cases and examples. Read more in Names.
  • Make sure your writing meets accessibility standards and requirements. Learn more in Write accessible documentation.
  • Avoid biased words, terminology, and language in your writing. Review the following sections on this page.

Determining whether a term shows bias

When writing Splunk docs, be aware of your own biases in your writing. Just because a term isn't offensive to you doesn't mean that it isn't problematic for someone else. To determine whether a term shows unconscious bias or harms a marginalized or underrepresented group, consider the following points:

  • Don't use words that diminish the historical or current situations of others. For example, use "peer" instead of "slave".
  • Don't use words that place a positive or negative connotation on color, race, or people. For example, write "deny list" instead of "blacklist".
  • Don't use words that imply otherness or that exclude a group. For example, use "everyone" instead of "mankind".
  • Don't use words that harm, degrade, or insult anyone or any group, whether it be mental, physical, sexual, functional, or criminal. For example, use "placeholder data" instead of "dummy data".
  • Don't use words that imply elitism or a position of power. For example, write "primary" instead of "master".

There's a lot of nuance and complexity in the evolving English language, so if a word doesn't fit one of these examples and it makes you uncomfortable, don't use it. If someone tells you that a word makes them uncomfortable, take their opinion as an opportunity to learn. Research the term and discuss its usage with an editor. Everyone deserves documentation that speaks to them rather than against them.

Alternatives to biased language

The following table provides examples of biased language along with suggested alternatives. The examples in the table aren't exhaustive, but instead are meant to act as a starting point to help you consider how to use inclusive language in your writing.

You might have questions about other types of words, such as violent language, potentially distressing terminology, or phrases that mention a color. Those terms are not inherently biased and aren't listed in this table, but you are always welcome to write with more thoughtful language. Look for other terminology replacements in the Usage dictionary.

Biased word or phrase Use this language instead Type of bias
Abnormal Atypical, not typical Ableist, disparaging
Blacklist Deny, deny list, reject, exclude Color bias, racist
Dummy data Placeholder data Disparaging
First-class entity Top-level entity Divisive
Flesh-colored, skin-toned Dark brown, cream, beige Color bias
Grandfathered Exempt Gendered language, racist
He, him, his, she, her, hers You, your, they, their, them, a user, the users Gendered language, sexist
Illegal characters Special characters Disparaging
Mankind All, everyone, humanity, humankind Gendered language, sexist
Master Manager, primary Divisive, racist
Master branch Main branch Divisive, racist
Sanity check Review Disparaging
Slave Peer, replica Divisive, racist
Whitelist Allow list, allow, accept, include Color bias, racist

Documenting biased language in the product

Teams at Splunk are working to remove biased language embedded in Splunk products. As a writer, you might see biased terms in the Splunk product code or in third-party products that you can't change or ignore. In these cases, use unbiased language wherever you can to stop perpetuating the use of a biased term.

Splunk documentation matches the product. If you're referring to a field, a setting in a .conf file, a UI element, or any other part of a Splunk product, or if you have to refer to an outside source or system that contains a biased term, you must use the exact name from the product for clarity. In all other cases, such as when describing a functionality rather than a specific part of the product, use unbiased language instead.

Last modified on 09 November, 2022
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This documentation applies to the following versions of Splunk® Style Guide: current


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