Background.
Even as OSM is rapidly growing in content and contributors, its credibility has been one of the main concerns for authoritative users. The belief that it is made by volunteers can limit the trust in the value of this free data source within traditional GIS communities. At HOT, we have prioritized the top 10 data quality aspects that we want to minimize. These aspects have been categorized under 3 categories the are Positional Accuracy, Semantic Accuracy, and Completeness.
We came to reach the top 10 list through a number of consultations with the Data Quality Working Group, representative from open mapping communities, and associates from HOT regional Hubs.
This information has been shared for reference by all OpenStreetMap data contributors, and users across the open mapping ecosystem, data quality associates at the HOT Regional Hubs, HOT partners and other communities that engage with OpenStreetMap.
HOT is focusing on prioritizing these aspects and implementation on how to minimize/eliminate them through HUB centered community engagements in form of trainings, collaborating with partners and developing tools that can be used to improve the quality of mapping.
There are many other issues affecting the quality of OSM data, however, our top 10 data quality aspects are;
3. Feature tracing inconsistencies.
5. Completeness of health facilities.
6. Completeness of public service data for sustainable communities.
7. Administrative boundary inconsistencies.
9. Logical consistencies of map features.
10. Tasking Manager project consistencies.
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1. Spatial Offsets:
An offset is the degree of deviation of an object from its intended position.

