To understand the physical mechanisms governing fluid-induced seismicity at field-scale fluid injection projects, we conducted fluid-induced fault slip experiments in the laboratory on critically stressed saw-cut sandstone samples with high permeability using different fluid pressurization rates. The data archived here acts as supplementary material to Wang et al. (2020; https://doi.org/10.1029/2019GL086627). Experiments were conducted at room temperature using a servo-hydraulic tri-axial deformation apparatus (MTS) equipped with a pore pressure system (Quizix pumps) at Experimental Rock Deformation Laboratory, GFZ. To investigate the correlation between fault slip and fluid pressure, we applied two different fluid injection schemes (hereafter tests “SC1” and “SC2”, respectively). ‘TestSC1’ refers to the fluid-induced fault slip experiment performed at fluid pressurization rate of 2 MPa/min while ‘TestSC2’ indicates the fluid-induced fault slip experiment performed at fluid pressurization rate of 0.5 MPa/min. The other boundary conditions for both experiments are similar. In addition, to simultaneously record acoustic emission (AE) events induced by artificial fault slip, 16 piezoelectric transducers (PZTs, resonance frequency ~1 MHz) contained in brass cases were directly mounted to the surface of samples, ensuring full azimuthal coverage for AE events. AE waveforms were amplified first by 40 dB using preamplifiers equipped with 100‐kHz high‐pass filters and then recorded at a sampling rate of 10 MHz with 16‐bit amplitude resolution. Each experiment lasted for about 4 hours. Throughout the experiment, mechanical data (measured by MTS) and hydraulic data (measured by Quizix pump) were all synchronously monitored with a sampling rate of 10 Hz whereas acoustic emission data were recorded with a sampling rate of 10 MHz. All results shown are recorded as a function of experimental time. The data are provided in tab-separated ASCII-Format (.txt). 2020-002_Wang-et-al_TestSC1.zip and 2020-002_Wang-et-al_TestSC2.zip are composed of 7 txt files and 8 txt files, respectively, as described below in Table 1. The first column represents time in second and the subsequent columns are indicated by the corresponding header at the first row. The second row indicates the unit for each column data. The raw data was processed with MATLAB. The algorithms we implemented include the moving average method, statistical regression and our developed MATLAB-based codes.