Import/Catalogue/Harare Water Wells

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Introduction

The project will import community water points or wells in Harare, Zimbabwe. Médecins Sans Frontières (MSF) have been monitoring and maintaining water points in Harare in response to cholera and typhoid outbreaks in recent years. They have collected data on the locations, infrastructure and operational arrangements for 458 water points in Harare.

Goals

The goal of this project is to: Import all 458 water points and conflate them with the existing water points in Harare. Update all water points on a regular basis in future.

Schedule

  • 4 February 2019 - Explicit permission obtained from MSF
  • XX XXX 2019 - Import plan submitted for review on the Import list - link
  • XX XXX 2019 - Planned start of import

Import Data

Background

Water point locations and attributes have been collected by MSF in their water and sanitation activities in Harare. The data is curated by MSF which they use for mapping and modeling. The database was made available for importing into OSM in March 2019.

  • Data source: Médecins Sans Frontières (MSF)
  • OSM attribution (if required): Contributors#MSF
  • Data License: Public Domain

Data files

Data was shared a comma separated values (csv) file with latitude, longitude and other attributes which can be opened in JOSM using the Open Data plugin. The data is available here.

Data quality

The MSF dataset is the most up-to-date data available for water points in Harare. It is also likely to be the most accurate as it is actively used for water and sanitation activities by MSF and other organizations. Therefore, it is proposed to let the coordinates of the MSF dataset override the coordinates in OSM for conflation during the initial import.

Import type

The initial import and conflation is a one-time import.

Data preparation

Data reduction and simplification

The MSF data contains a lot more information than needed for OSM import.

Tagging plans

Each water point will be tagged as man_made=water_well.

Tagging table
Object Tagging MSF data attribute Comment
Water Point/Well man_made=water_well
ref=* ID Unique reference number/ID for each water point
pump=* Infrastructure in place E.g. hand pump or electrical/submersible pump
pump:status=* Working status of borehole If the pump is working or not working
drinking_water=* Type of water usage If drinking water is available from a well

Changeset Tags

The changesets will be uploaded using the account XXX and will be tagged with:

description=Water Point/Well import
source= Médecins Sans Frontières (MSF)
source:date=2019-xx-xx
import=yes

Data merge workflow

Team approach

The import will be done by one person using the JOSM Conflation plugin.

Workflow/Conflation

  1. Download OSM data for Harare in JOSM using the Overpass API with a query that includes man_made=water_well and amenity=drinking_water in Harare in the wizard.
  2. Open the csv file containing water point/well data from MSF
  3. Configure the conflation plugin to generate matches:
  4. The existing wells/OSM layer is the Subject
  5. The new well data is the Reference
  6. The distance is set to 50 meters
  7. Select matching wells and check them manually before conflation
  8. Conflate all other wells

Updates

Water point data will be maintained and updated with the help of the OSM community in Zimbabwe and the MSF team.