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Databases covering all individuals of a population are increasingly used forresearch and decision-making. The massive size of such databases is oftenmistaken as a guarantee for valid inferences. However, population data havecharacteristics that make them challenging to use. Various assumptions onpopulation coverage and data quality are commonly made, including how such datawere captured and what types of processing have been applied to them.Furthermore, the full potential of population data can often only be unlockedwhen such data are linked to other databases. Record linkage often impliessubtle technical problems, which are easily missed. We discuss a diverse rangeof misconceptions relevant for anybody capturing, processing, linking, oranalysing population data. Remarkably many of these misconceptions are due tothe social nature of data collections and are therefore missed by purelytechnical accounts of data processing. Many of these misconceptions are alsonot well documented in scientific publications. We conclude with a set ofrecommendations for using population data.

Big Data is not the New Oil: Common Misconceptions about Population Data