Import CAR UNICEF FOSA
Goals
This is the first import for Central African Republic done as a part of the EUROSHA project. Its goal is to include the UNICEF data for health facilities for half of Central African Republic into OSM. The goal is also to find effective procedure later to be used for UNICEF data for schools and water points.
Schedule
- Preparation, discussion - March, beginning of April 2013
- Import - expected start in April 2013
Import Data
Data description
The dataset consists of 343 nodes for 6 regions (prefectures) of CAR: Mambere-Kadei (46 nodes), Nana-Gribizi (27 nodes), Nana-Mambere (47 nodes), Ouaka (60 nodes), Ouham (74 nodes) and Ouham-Pende (89 nodes out which 1 not to be uploaded because of missing information on health facility type).
The dataset contains followin attributes: ID, WPT, CODE, FOSA_CODE, LAT_DD, LONG_DD, PAYS, PREF, S_PREF, COMM, VILLE_VILL, QUARTIER, POP_VILLE_, STATUT_FOS, TYPE_FOSA, TYPE_FOSA_SHORT, NOM_FOSA, NB_LITS, NB_PERS_SO, NB_PATIENT, COMITE_WAS, NB_PERS_WA, LTA,VIP, VIP_PLEIN, LATRINES_S, LAVE_MAINS, INCINERATE, BAC_A_ORDU and TOTAL_LATR.
Background
ODbL Compliance verified: YES
The authorization given by UNICEF CAR was approved by the OSMF License Working Group as ODbL compatible.
Import Type
This is a import done manually in JOSM, through a specific Tasking Manager job, according to a workflow document.
Data Preparation
Data Reduction & Simplification
The data will be reduced only to the keys listed below.
Tagging Plans
Considering the accuracy of the location is sometimes coarse and the objects have to be moved, a fixme will be created with the UNICEF pair of coordinates as values so that the contributors can have a track of the original location.
In the spreadsheet below, No values are not counted within the number of objects.
| Unicef Key | Unicef value (number) | OSM tag |
|---|---|---|
| all objects | amenity=hospital | |
| all objects | source=UNICEF | |
| ID | not tagged because not relevant | |
| WPT | not tagged because not relevant | |
| CODE | not tagged because not relevant | |
| FOSA_CODE | not tagged because not relevant | |
| LAT_DD | not tagged because not relevant | |
| LONG_DD | not tagged because not relevant | |
| PAYS | not tagged because not relevant | |
| PREF, SOUS_PREF, COMM, VILLE_VILL, QUARTIER | addrːfull=* | |
| VILLE_VILL | addr:city=* | |
| POP_VILLE | not tagged because not relevant | |
| STATUT_FOS | Public (306) | operator:type=government |
| STATUT_FOS | Prive (37) | operator:type=private |
| TYPE_FOSA | Poste de sante (204) | health_facility:type=dispensary |
| TYPE_FOSA | Centre de sante (with beds) (118) | health_facility:type=health_center |
| TYPE_FOSA | Hopital prefectoral (7) | health_facility:type=prefectoral_hospital |
| TYPE_FOSA | Hopital regional (3) | health_facility:type=regional_hospital |
| TYPE_FOSA | Clinique privee (1) | health_facility:type=private_hospital |
| TYPE_FOSA | No attribut (1) | not to upload |
| NOM_FOSA | name=* | |
| NB_LITS | numbers 0-179 | capacity:beds=* |
| NB_PERS_SO | not tagged because unknown meaning | |
| NB_PATIENT | not tagged because not relevant | |
| COMITE_WAS | Oui/Non | not tagged because not relevant |
| NB_PERS_WA | not tagged because not relevant | |
| LTA | not tagged because unknown meaning | |
| VIP | not tagged because unknown meaning | |
| VIP_PLEIN | not tagged because unknown meaning | |
| LATRINES_S | not tagged because not relevant | |
| LAVE_MAINS | Oui/Non | not tagged because not relevant |
| INCINERATE | not tagged because not relevant | |
| BAC_A_ORDU | Oui/Non | not tagged because not relevant |
| TOTAL_LATR | numbers 0-23 | toilets:number=* |
Changeset Tags
We will use the following changeset tags.
- comment=*
- created_by=JOSM/version
- source=UNICEF
- source:date=2012
- import=yes
- url=http://wiki.openstreetmap.org/wiki/Import_CAR_UNICEF_FOSA
Data Transformation
Data were received as a XLS sheet. Reduction, simplification, manual cleaning and tag transformation will be done directly in a copy of the XLS file. The two fields of coordinates will be renamed X and Y. Then the file will be converted into CSV and divided into 6 files based on the region. The 6 CSV files will be opened with JOSM as CSV files with the opendata plugin. Finally the files will be saved in the OSM format and ready for distribution/import.
Data Merge Workflow
Team Approach
The importation team consists of 5 EUROSHA volunteers: FRosenkranc, LenkaP, fedebasa, Jorieke V and MorganeG. The preparation is done by FRosenkranc with the support of SeverinGeo.
References
The import will be discussed in the import list.
Workflow
Please refer to the workflow page.
Reverse plan
In case of any trouble, JOSM reverter will be used.
Conflation
Unicef dataset has 343 nodes out of which 342 will be imported. In the 6 regions of CAR where import will be happening, the only health facilities mapped are those already mapped by Eurosha volunteers in cities taken by the rebels in December 2012. These cities are: Mbrès (region Nana-Grěbizi), Kaga-Bandoro(region Nana-Grěbizi), Batangafo (region Ouham) and Kabo (region Ouham). Only data in these cities will be manually merged.