A chart is only as good as the validity of its data. It’s important to check both the data and chart several times with multiple people before publishing. One small error can invalidate the integrity of an entire visualization. Several errors in data accuracy can damage credibility.
- Is this an accurate way to represent this data?
- Did someone else look at the chart and data for feedback?
- If there are percentages, do they add up to 100? Why not?
- What is the source of the data?
When using charts that show percentages, users expect things to add up to 100%. If they don’t it undermines the integrity of the visuals by leaving the user with missing pieces.
To remedy this effect add a note at the bottom to explain the missing data.
Example: Percentages may not sum to 100% due to rounding.
Use notes to add in other caveats around the data like if it was taken from a specific time period.
Example: Percent change is based on a 3 month period (October-December) and compared to the previous year.
Example: Company-level information should be considered in context of total complaints, company size and market share in a given geographic area.
Including the source of the data in the visualization is a must. It adds credibility and transparency to the graph. The visualization could then be replicated using the mentioned sources which adds credibility.
If you’re unable to link to the source, link to a spreadsheet of the data used
to create the visualization.