This brief report describes a lab created data base of "simulated" noise sources (reaction wheels primarily) for use in testing and validating magnetic noise identification algorithms for spaceflight. The data set is useful for the space magnetomter community. My main comments include expanding description of the quality and characteristics of the data (e.g., resolution and amplitude of noise signals), rationale for the layout of the four magnetometers, and providing example time series as well as the Tables describing the signals. See attached pdf for other minor comments and elaboration of the above.

Happy to answer questions on my comments - Mark Moldwin

This manuscript describes the creation of an open-source dataset of magnetometer interference signals. The dataset of stray magnetic field signals is exhaustive and enables many possible combinations of different interference and pseudo-geomagnetic field signals to test magnetometer interference removal algorithms. This work enables magnetometer scientists to test and develop their magnetometer payloads for a broad range of purposes from UAVs to spacecraft of many different volumes. 

My main recommendation is to include an example script / tutorial in the dataset that shows how to load the data and create different signal combinations. This script would improve the readiness and accessibility of the dataset to the scientific community. Please see the attached minor comments that ask for more descriptive captions, several citations, etc.

The magnetic cleanliness program is significant to achieve scientific objectives related to magnetic field measurements. It should be noted that magnetic tests are required to suppress stray magnetic fields. Furthermore, any gradiometric approach and magnetometers on long booms would guarantee magnetic field measurement without magnetic interference. However, the cost involved in performing such magnetic tests and adopting a long boom is likely to be high. To reduce the cost, therefore, recent missions adopt shorter booms. Hence, the authors generated an open-source dataset of stray magnetic field data, which is to be used to develop and validate magnetic interference mitigation algorithm. The dataset contains temporal variations of magnetic field corresponding to near-DC trends, synthesized interference, and pseudo-geophysical signals.

The significance of the open-source dataset of stray magnetic field data is highly evaluated.