The concept validity of a dataset or measurement tool is the extent to which the dataset or measurement tool measures what it claims to measure A [study on cycling safety in Canada](https://cyclingmagazine.ca/sections/news/winter-cycling-found-to-be-no-less-safe-than-cycling-in-the-summer/) concluded that the risk of cycling was no worse in the winter than in the summer, based on trauma injury data. Canadian Cycling Magazine cited this study to encourage its readers to continue riding in the winter. However, the dataset did not contain information on less severe bicycling injuries. Readers whose concept of "safety" includes avoiding any form of injury might consider the magazine's recommendations invalid given the limitations of the dataset. This study and the conclusion drawn by the magazine is an example of low concept validity, where the dataset is not in fact appropriate for the research question. Measures of trauma may not also be a valid measure "safety" in the broader sense.