Preventing misuse of your data

Use “warnings” to highlight crucial limitations that affect how users interpret the data. They prevent misuse of data, with minimal interruption to the content.

Warnings are designed to stand out from your analysis so that users notice them; using too many, or including too much detail, distracts users. Warnings should only be used at the end of the Main points or in the analysis sections. Avoid using hyperlinks in warnings, unless the link is directing users to more information in the Strengths and limitations section. 

If your bulletin contains designated Experimental Statistics, include a standard warning at the end of the Main points section (see Warnings about Experimental Statistics subsection). This is to let users know that the statistics and/or method are in development. 

For an example of how to include a warning box, see the Labour market overview, UK monthly bulletin.

How to write a warning


  • Highlight essential limitations of the data to help users avoid misinterpreting it.
  • Keep warnings short and clear; when text is hard to understand, people retain less information.
  • Only use warnings when they have a direct effect on how users interpret the content around them.
  • Include only relevant information; use the Measuring the data or Strengths and limitations sections, which you can link to in the warning, to add detail.
  • Only include warnings at the end of the Main points section, and in the analysis sections.
  • Include a standard warning for Experimental Statistics at the end of the Main points section.

Do not

  • Use warnings too often; it disrupts the reading experience, makes it difficult to understand the content and reduces the effectiveness of each warning.
  • Place warnings next to each other as they overwhelm users and get in the way.
  • Position warnings before your analysis; testing has shown that users find it confusing to read warnings before commentary.
  • Provide definitions in warnings; instead, define terms briefly in your analysis, and use the glossary section to provide more detail.
  • Include hyperlinked text to other sections or articles; instead, any further detail should be included in the Strengths and limitations section, or linked to from there.

Warnings should be short

Warnings have a strict character limit of 280 characters. The shorter the warning, the more effective it will be. Presenting too much information to users makes it less likely that they will understand and retain the warning. Long warnings are also problematic for users on mobile devices or with accessibility needs.

If you need to explain the limitations of the data in more detail, expand on it in the Strengths and limitations section.

The content design team can help you to write short, effective warnings – contact if you want to discuss a warning you are working on.

We are constantly improving based on research and best practice. Any significant changes to our guidance are available on the Updates page.

Warnings about Experimental Statistics 

Use a warning box after the Main points to highlight if your bulletin contains Experimental Statistics. These are a type of official statistics that are going through development and evaluation. 

For Experimental Statistics, use: 

“These are Experimental Statistics. The [method/data source/estimates is/are] currently under [review/development], which means [brief detail about how this affects estimates or data quality]. We advise caution when using the data.” 

More information on the methods used and quality limitations of the data can be included in the Strengths and limitations section.

Experimental Statistics should always be primarily published as a bulletin where they are the first release of new data. An article using the data can be published alongside the bulletin if more detailed analysis is needed. 

Next section: Data and methodology