# 3.5. Missing Data

When mean or filtered values are to be calculated, the question of how to handle missing data arises. For a number of reasons it is difficult to devise a simple objective rule that can be applied to all cases. INTERMAGNET recommends a simple and pragmatic approach: mean or filtered values may be calculated when 90% or more of the values required for calculation are available. This can be interpreted as either 90% of the values or 90% of the weight of the filter. When fewer than 90% of the required values are available the value should be assigned the value used to flag missing data. INTERMAGNET recommends adoption of this rule for both simple mean and weighted mean calculations. For example, a simple daily mean value may be computed when 1296 or more one-minute values are available for the day. Similarly, if a one-minute value is constructed from one-second samples, the one-minute value may be computed when 54 or more one-second samples are available. In either case the weights applied to each sample in the mean or the filter must be re-normalized to account for the reduced number of samples available. In practice, this means dividing the sum of samples by the number of available samples in the case of a simple mean or normalizing to unity those coefficients that have been used in a filter calculation. INTERMAGNET observatories are expected to provide high levels of data continuity, so this rule is expected to be applied only rarely. To avoid the propagation of missing values into higher level means, it is recommended to calculate all higher level means using the method described in Section 6.6.