Longitudinal assessment of quantitative imaging biomarkers (QIBs) requires a comprehensive quality control (QC) program to minimize bias and variance in measurement results. In addition, the availability of data analysis software from multiple vendors emphasizes the need for a means of quantitatively comparing the computed QIB measures produced by the applications. The purpose of this work is to describe a digital reference object (DRO) that has been developed for the evaluation of arterial spin-labeling (ASL) measurement results. The ASL DRO is a synthetic data set consisting of 10 × 10 voxel square blocks with a range of ASL control image signal-to-noise ratio (SNRControl), blood flow (BF), and proton density (PD) image SNR values (SNRControl:1-100, BF:10-210 ml/100 g min-1, SNRPD:10-100). A pseudo-continuous ASL sequence was simulated with acquisition parameters and modeled signal intensities defined according to those typically associated with clinically-acquired ASL images. ASL parameters were estimated using the commercially-available nordicICE software package (NordicNeuroLab, Inc, Milwaukee, WI). Percent bias measures and Bland-Altman analyses demonstrated decreased bias and variance with increasing SNRControl and BF values. Excellent agreement with reference values was seen for all BF values above an SNRControl of 5 (concordance correlation coefficient greater than 0.92 for all SNRPD values). The ASL DRO developed in this work allows for the evaluation of software bias and variance across physiologically-meaningful BF and SNRControl values. Such studies are essential to the transition of quantitative ASL-based BF measurements into widespread clinical research applications, and ultimately, routine clinical care.