The NGA-Subduction time series have been used to create this dataset of equivalent number of uniform cycles. Cyclic shearing caused by earthquake shaking can cause pore pressure build up and liquefaction in cohesionless soils, strength and stiffness degradation in cohesive soils, and fatigue damage in structures. Seed et al. (1975) proposed a method to convert an earthquake time series to an equivalent number of uniform cycles (neq). The main concept is that neq uniform cycles at a given cyclic stress ratio (CSR = applied shear stress, τ, divided by the vertical effective stress, σ'v) predict the same amount of damage as the actual ground motion. The first step of the method is to convert an acceleration time series to a series of uniform cycles at different amplitudes using a cycle counting method (CCM). The second step is to sum the number of uniform cycles at different amplitudes to predict an equivalent number of uniform cycles at a single amplitude using a weighting factor curve (WFC). Stelzer et al. (2020) showed that different CCM with the same WFC can predict neq values with average differences up to 35%. Therefore, there is a large amount of epistemic uncertainty based on the choice of CCM to convert an acceleration time series to a series of uniform cycles at different amplitudes. Due to this uncertainty, and to make the database more applicable to all types of analyses, we use four different cyclic counting methods: peak counting, mean-crossing, level crossing, and rainflow counting. This allows practitioners to pick the CCM that is most appropriate for their application and site, or use several to include epistemic uncertainty in their analyses. In addition, we use three different duration filters, resulting in 12 different measures of uniform cycles per acceleration time series. Finally, we provide both the raw data, and the aggregated number of cycles per amplitude bin, where we have chosen 10 amplitude bins evenly spaced between 0 and the PGA of the acceleration time series.