The Super Dual Auroral Radar Network (SuperDARN) was built to study ionospheric convection and has in recent years been expanded geographically. Alongside software developments, this has resulted in many different versions of the convection maps dataset being available. Using data from 2012 to 2018, we produce five different versions of the widely used convection maps, using limited backscatter ranges, background models and the exclusion/inclusion of data from specific radar groups such as the mid-latitude radars. This enables us to simulate how much information was missing from previous decades of SuperDARN research. We study changes in the Heppner-Maynard boundary, the cross polar cap potential (CPCP), the number of backscatter echoes (n) and the χ-squared/n statistic which is a measure of the global agreement between the measured and fitted velocities. We find that the CPCP is reduced when the polar cap radars are introduced, but then increases again when the mid-latitude radars are added. When the background model is changed from the RG96 model, to the most recent TS18 model, the CPCP tends to decrease for lower values, but tends to increase for higher values. When comparing to geomagnetic indices, we find that there is on average a linear relationship between the Heppner-Maynard boundary and the geomagnetic indices, as well as n, which breaks at high values (e.g. HMB ~50 degrees) due to the low observational density. We find that whilst n is important in constraining the maps (maps with n>400 are unlikely to change), is insufficient as the sole measure of quality.