Contributor from Bamako, Mali
Add Schools of Mali with metadata.
- 10,156 schools with GPS location.
- Proper metadata (operator, type, academy, cap, latrines, nb of pupils, etc)
- Data is relatively recent (2013)
- Data is almost inexistent in OSM
- We have a group of people ready to enhance it directly in OSM for Bamako area.
- We have a couple NGOs in need for this and willing to contribute to.
- There's apparently no Mali community besides HOT but it's not related to HOT.
- Data is very simple: only GPS coordinates with metadata.
- No shapes, no relations, only points.
- Data is ready.
- Need to validate some of the data with author.
- Tested successfuly on Dev Server.
Data source site: https://github.com/jokkolabs/mali_schools/raw/master/MLI_schools.csv
Data license: https://raw.githubusercontent.com/jokkolabs/mali_schools/master/LICENSE
Type of license: Public Domain (CC0)
ODbL Compliance verified: yes
OSM Data Files
- one-time import
- using ./upload-python2.py (tested on master.apis.dev successfuly)
- using dedicated account "opendatamali"
Data Reduction & Simplification
- OSM XML files only contains nodes and selected metadata.
- All files represent ~ 10K nodes for about 10M.
- Data looks OK in jOSM
- Carefully searched for similar tags in taginfo.
- Reusing the following tags/values:
- drinking_water:type=tap|working_drilling|inexhaustible_well|exhaustible_well (new values!)
- One changeset file per academy (17)
- Largest file is 1.2M, 1214 nodes.
Transformation of CSV data to OSM XML is done through a very simple Python script https://github.com/jokkolabs/mali_schools/blob/master/csv2osm.py
- Generate changeset files (OSM XML) : 17
- Loop through changeset files
- upload using bulk_upload.py
- check for failed uploads
- manualy delete/retry erroneous changesets