Optical mapping data is used in many core genomics applications, including structural variation detection, scaffolding assembled contigs, and mis-assembly detection. However, the pervasiveness of spurious and deleted cut sites in the raw data, which are called Rmaps, make assembly and alignment of them challenging. Although there exists another method to error correct Rmap data, named cOMet (Mukherjee et al., GigaScience, 7(6), 2018), it is unable to scale to even moderately-large sized genomes. The challenge faced in error correction is in determining pairs of Rmaps that originate from the same region of the same genome.