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"When we saw those maps, we were just speechless," said Zuber.
The maps we were given were practically useless: many streets lack names, and the route described did not account for Rome's many one-way streets.
By integrating these two maps, we were able to quantify the impacted areas in relation to the geodiversity.
By comparing the predicted and observed maps we were able to examine how well our predictions fitted the observed mortality and in which regions there were mismatches.
Using these maps, we were able to anchor an additional 440 scaffolds from the kiwifruit draft genome assembly.
Using these maps, we were able to replicate the identification of previously known genes that affect flowering time in maize and improve the resolution of QTL mapping.
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We are just beginning to grasp what it means to live in a world in which maps are everywhere – and in which, by using maps, we are mapped ourselves.
With the rise of OpenStreetMap, the brilliant and constantly improving Wikipedia of maps, we are all cartographers now.
The large majority of maps we're working with in this project are fire insurance maps, which were designed to give insurance adjusters a reasonable metric to assign fire insurance values to buildings.
Using these motif maps, we are able to also access challenging loci where existing technologies fail.
With LD-based maps, we are able to characterize the genome-wide fine-scale recombination landscape in D. pseudoobscura and D. miranda for the first time.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com