As a crowd-sourced data project, OpenStreetMap (OSM) is reliant on volunteers, from a variety of backgrounds, to contribute and maintain the data. This can lead to potential gaps in the quality of the data, as there is no centralized process for verifying or correcting the information that is contributed. This can lead to inaccuracies or inconsistencies in the data, making it difficult to use confidently.

Additionally, depending on the level of volunteer participation in those areas, there may be gaps in coverage or incomplete fixed data issues. This can limit the data's usefulness for certain applications such as mapping, analysis, research, and so on. To address these issues and increase the number of contributors, a low-barrier methodology for improving the quality of OpenStreetMap data is required. Finally, it can assist OpenStreetMap communities in maintaining and improving OSM data in their own areas.

Open Mapping Hub Asia-Pacific (AP Hub) aims to support OpenStreetMap (OSM) and open mapping initiatives in the region as part of our efforts to advance this movement. AP Hub also offers a method for enhancing the quality of data on OpenStreetMap when data quality review is a regular task. AP Hub methodology for enhancing the quality of OpenStreetMap data includes: * Boost the number of experienced mappers who routinely resolve data quality issues. * Help partners and communities with open mapping for their particular data requirements, such as in HOT's Impact Areas.

Our Approach

Data Quality Assurance: Review the OpenStreetMap data to identify, minimize, and avoid recurring data quality issues. JOSM validator is in nearly all aspects the most powerful and the most useful validator available for mappers. For more issue detection in JOSM there is an option to activate JOSM Validator. Communities can address identified issues in order to encourage people to validate and improve their abilities via gamification using Osmose data in MapRoulette. Please bear in mind do not map for validator tools, it has false positives. Only fix real errors which you understand and know how to improve correctly.

How To Ensure Data Quality in Mapping Events/Activities: Although initially supported by individuals, the continued growth and popularity of OpenStreetMap has also given rise to organized mapping efforts companies, academics, local organizations, etc. geared towards working on OSM. Checklists are being used to assist in data quality checks for data contributions. For this kind of activity, can use these additional steps

• Pre-event. Focus to check the existing OpenStreetMap data and prepare public documentation.
• During the event. Focus to provide early warning for any questionable editing and prevent it from repeating.
• Post-event. Validate the mapping result, maintain all feedback (changeset discussion, Tasking Manager discussion, etc), and update the public documentation.

Building better mapping resources by providing resources, tools, and training to create good data in the first place.

• HOT Data Models to cover the most common features mapped in OpenStreetMap across HOT's five impact areas.
• Encourage Tasking Manager onboarding for new project’s manager and author in Tasking Manager.
• Advanced training for mappers to increase capacity for mappers to do complex editing and validation. Some ideas for training sessions include, but not limited to : backup JOSM setting, Sandbox for editing, Data History, and Plugin Reverter.

Transparency: Participate in the OpenStreetMap community by sharing mapping activity on the platform using the changeset discussion, OpenStreetMap Wiki, OpenStreetMap channel, etc. As part of the OpenStreetMap community, also being proactive with the existing quality assurance tools could help the development of community-driven tools. You can contribute by submitting ideas or reporting bugs to the developer team.

For more information, please see this OSM Wiki page.