Mobile mapping is the process of collecting geospatial data from a mobile vehicle using a 360º camera, laser scanner, GPS/IMU positioning system, and other sensors. This is one of the most time and cost effective methods to collect geospatial data, but the required equipment can be expensive. An alternative approach to mobile mapping brings the opportunity to the OpenStreetMap community to "Map in 360" using a wide range of consumer devices compatible with Mapillary. Instead of capturing a frame of street-level imagery in a single direction, a 360º camera can capture the entire scene simultaneously. 360º street-level imagery provides the OpenStreetMap community a more comprehensive understanding of the map space and more accurate machine-generated map data. In this talk, we will review the workflow of data collection with 360º cameras, look at how to upload 360 street-level images to Mapillary, and compare the impact of different 360º camera models in terms of map data extraction accuracy. OpenStreetMap communities can use this knowledge to coordinate their own street-level imagery collection with 360º cameras to contribute to Mapillary and improve local maps.