Are the appropriately processed (detrended, artifacts removed, …)? This requires careful thought, often with domain expertise, about what problem is being solved. E.g., many time-series analysis algorithms will be dominated by underlying trends if underlying trends in time series are not removed. In general, properties of the data, especially if they're likely to affect many time-series analysis algorithms (like underlying trends, artefactual outliers, etc.) should be removed if they're not informative of the differences you care about distinguishing.