Import Nigeria eHealth Bauchi Health Facilities
Goals
The goal is to import 1,096 health facilities collected by eHealth Africa for the Bauchi State, Nigeria.
Schedule
- Preparation, discussion: This import is almost identical to the Kano State one, so we don't expect any issues.
- Import - expected to start on Monday, 1st of September 2014.
Import Data
Data description
The datasets are drawn and generated by eHealth Africa in the course of their mapping activities in Northern Nigeria. The organisation has performed data collections in the entire area and remote tracing using aerial imagery. For the Bauchi state, a Q&A has been performed to double-check the accuracy of this data.
The original dataset consists of 1,096 health facilities entries, in .csv format.
The dataset contains several field attributes, like the name of the facility, the health facility type, the ward, LGA and state to which it belongs and the ownership.
Background
ODbL Compliance verified: YES
eHealth Africa has given full authorization for the use of their data with the standard authorization document of the Humanitarian OpenStreetMap Team (HOT). A scan of the document can be found here.
Import Type
The import will be done manually through one job in the HOT Tasking Manager (TM), having for each task of the job only the health facilities nodes that lie within the task tile, in a similar way as it was done for the Central African Republic UNICEF import. For each task, we will first check the eHealth nodes to be imported, and second we will assess the data already in the OSM database against the eHealth Africa one for the merging of the eHealth data into the OSM database. The OSM mappers who will contribute to this import job will follow a detailed workflow to accomplish this.
Data Preparation
Data Reduction & Simplification
The data is originally in csv format, in only one file for the whole Bauchi state. Some internal eHealth Africa codes were deleted for being not relevant for the import.
Tagging Plans
Each health facility will have the following tags:
| eHealth Africa key | OSM tag | Observations |
|---|---|---|
| All objects | amenity=hospital | |
| All objects | source=ehealthafrica.org | |
| Sources | source:date=* | Some have been collected in 2013 and others in 2014 |
| StateName | addr:state=* | |
| LGAName | addr:district=* | Local Government Area (LGA) |
| WardName | addr:municipality=* | Ward |
| WardName, LGAName, StateName | addr:full=* | |
| HthFa_Name | name=* | |
| Alternative name | alt_name=* | Only some facilities have an alternative name |
| HthFa_Type | health_facility:type=* | Health Post will be translated by dispensary, Primary Health Centre by health_centre and General Hospital by hospital. |
| HthFa_Ownership | operator:type=* | Only two values: public or private |
Changeset Tags
We will use the following changeset tags:
- comment=eHealth Africa Bauchi health facilities import, #hotosm-task-637
- created_by=JOSM/version
- source=ehealthafrica.org
- import=yes
- url=https://wiki.openstreetmap.org/wiki/Import_Nigeria_eHealth_Bauchi_Health_Facilities
Data Transformation
Data is in csv format. We just process the csv file and convert it to osm format with a gawk script.
Data Merge Workflow
Team Approach
Import will be undertaken by experienced OSM mappers, using a import specific OSM user account, following a workflow and working through a HOT Task Manager job similar to the ones set for the import of UNICEF health facilities, schools and water resources in Central African Republic.
References
The import will be discussed in the import list and in the Talk-Ng list.
Workflow
You can see the workflow here.
Reverse plan
In case of any trouble, JOSM reverter will be used.
Conflation
The location of the eHealth nodes is generally correct, but following the already mentioned workflow, we will place the nodes in the exact position. For example, for a hospital compound, we will place the node more or less at the centre of it, in case it is not centered.
If other health facilities are encountered, they will be compared with the import ones and merge the data in the best possible way, keeping all info that the old ones may have. In case of doubt, a fixme tag will be placed, the issue will be reported through the comment of the task (tile) of the TM job, and the user that uploaded the old health facility node would be eventually contacted if needed.