In order for OpenStreetMap to thrive, we need to attract and retain new mappers. To be welcoming to newcomers, we should avoid high barriers to starting mapping and instead support contributions that can be made with limited time, context, and experience. StreetComplete is a great example of this approach: by asking simple, well-scoped questions, it enables contributors to improve data quality in small, incremental steps. An effort-inclusive tagging philosophy builds on this idea by encouraging tagging schemas where each additional piece of information can be added independently and still be useful on its own. For example, amenity=bench is still a bench regardless if mapper knew about backrest=* and armrest=*.

I am writing this because I have encountered cases where newcomers are advised to follow practices that I consider unnecessarily demanding for basic contributions. A particularly stark example appears in the context of CCTV and ALPR mapping, where a sub-community recommends mappers to take high-resolution photographs, research manufacturers and exact models at home, and consult product datasheets for adding a single camera to OSM. While such detailed work can be valuable, it not only risks discouraging participation, but also makes incorrect data harder to detect if mapper misidentifies the model.

Advanced mapping techniques such as per-lane destination tagging or 3D mapping are entirely appropriate in contexts where that level of detail is the goal. The problem arises when tagging schemas or community conventions require large changes or trolltag-esque top-level tag replacement in order to express additional information. A common example is waste baskets that support sorting: in order to describe what kind of waste is collected, some tagging convention implies to replace amenity=waste_basket with amenity=recycling, rather than incrementally enrich the existing object. Tagging practices like this make small improvements harder and counter an effort-inclusive, iterative approach to improving OSM data.