Import CAR UNICEF FOSA

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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

  1. Preparation, discussion - March, beginning of April 2013
  2. 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.

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 sev_hotosm from the Humanitarian OSM Team.

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.