This dataset was used to support the findings in "Harnessing Machine Learning to Predict MoS2 Solid Lubricant Performance" by Vogel et. al." It includes process, microstructure and property information for physical vapor deposited molybdenum disulfide solid lubricant coatings, and represents a subset of the experimental data described in "Microstructural Assessment of Molybdenum Disulfide Coatings Using Nanoindentation Hardness" by Babuska et. al. MoS2 samples were deposited under a variety of deposition conditions, including varied deposition type, argon pressure, sputter power, substrate bias, and total target usage. Tribological testing and materials characterization was performed to obtain a variety of properties including hardness, reduced modulus, wear rate, density, stoichiometry and coefficient of friction values. The data for 1-3 runs of 10000 friction testing cycles is available for a subset of the samples included here. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.