Any system that makes it easy for you to put your data in should make it equally easy for you to take your data out. https://twitter.com/billdollins/status/1660962579894743040
One of the significant challenges with OpenStreetMap (OSM) is the difficulty in splitting the data into smaller, manageable areas and keeping up with updates specifically for those areas.
See more here – Problems with maintaining the regional extract in an up-to-date state - #10 by andygol
OSM serves as a centralized repository of global geospatial information, encompassing a vast amount of data from all around the world. While this comprehensive dataset has numerous benefits, it can present difficulties when attempting to extract and maintain data for specific regions or smaller areas.
For local communities, organizations, or businesses that have localized needs, managing the entire global dataset of OSM becomes unnecessary and cumbersome. Extracting only the relevant data for a particular area can be a time-consuming and complex task, requiring substantial effort and technical expertise. Furthermore, once a subset of data is obtained, it becomes challenging to keep it up to date with the ongoing updates and changes in the global OSM dataset.
Staying synchronized with these updates for a small, localized area can be demanding, especially for individuals or organizations without dedicated resources or technical support. The process of monitoring changes, merging updates, and ensuring data accuracy becomes a considerable challenge, potentially resulting in outdated or inconsistent data for the specific area of interest.
Addressing the problem of data being a single pool that is hard to split and keep up with updates for small areas requires a multi-faceted approach. It involves the development of more efficient tools and techniques for extracting localized datasets, refining existing data management workflows, and enhancing collaboration within the OSM community.
Improving the accessibility and usability of tools specifically tailored for extracting and maintaining localized OSM data would greatly benefit individuals and organizations working on smaller scales. These tools should simplify the process of selecting and retrieving data for specific areas, automatically track updates, and enable seamless integration of local updates into the larger OSM dataset.
Additionally, fostering collaboration and knowledge sharing within the OSM community can help address this challenge. Encouraging the development and adoption of best practices, guidelines, and standards for managing localized data would enhance the ability of users to maintain accurate and up-to-date datasets for their specific regions.
The cohesive nature of OSM’s global dataset poses a challenge when it comes to splitting the data and keeping up with updates for small areas. Overcoming this problem requires the development of user-friendly tools, refining data management workflows, and fostering collaboration within the OSM community to ensure that localized datasets can be effectively extracted, updated, and utilized.
Reevaluating the OSM data model and data storage infrastructure is crucial in order to effectively address the challenges discussed above. For those interested, there is is my ideas about organization data storage and processing - OSM 2.0 API using git.