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The method that is typically employed for ensuring data integrity while logging is through error checking mechanisms. This approach validates the accuracy and consistency of data during the logging process. Error checking helps in identifying any discrepancies or corruptions in the data, ensuring that what is recorded reflects the true state of the monitored variables.

Implementing error checking methods, such as checksums or parity bits, allows for the detection of errors introduced during data transmission or storage. When logging data, maintaining integrity is crucial, especially in applications like industrial automation or scientific research, where erroneous data could lead to faulty conclusions or operational failures.

Each of the other methods has its specific purposes, but they do not primarily focus on ensuring data integrity. Data compression techniques aim to reduce the size of the data to save storage space, while redundant data storage involves keeping copies of data to prevent data loss in case of failures but does not inherently verify the data's accuracy. Continuous monitoring refers to the real-time observation of data but does not directly address the integrity of the logged data itself.