Using the ohsome framework to develop an OSM Confidence Index to support humanitarian mapping
2021-09-30, 15:00–15:30, Puerto Madryn

Alongside the OpenStreetMap community, the users of OSM data are manifold: from academics to businesses and humanitarian actors. The OSM community has over 1 million active contributors, around 50,000 of which are active each month. Four out of the "big five" mega-corporations are already using OSM data in their products and are actively contributing to the OSM data set.

OpenStreetMap data is used more and more widely, which means that data quality and fitness-for-purpose analyses are becoming more and more relevant. Many scientific papers have been written about OSM data quality, but most only apply methods to few small regions, and results are available for the single point in time when the papers are published. Results are often not easy to replicate, e.g. to check the transferability of a method to other regions. Ideally, one would like to calculate data quality measures on a global context in a fine spatial (and temporal) resolution.

This talk will present how HeiGIT and MapAction are addressing OSM data quality questions with the open source ohsome platform to perform in depth data analysis of spatio-temporal statistics of the OSM geo data set.

The Ohsome Quality analysT (short OQT) is the name of a new software implemented by HeiGIT that is based on the ohsome framework. Its main purpose is to compute quality estimations on OpenStreetMap (OSM) data. Any end user such as humanitarian organisations, public administrations, as well as researchers or any other institution or party interested in OSM quality can use the OQT to get hints on the quality of OSM data for their specific region and use case.

The original idea for the OQT developed out of a simple use case: Having a one-click tool that can give information on the quality of the OSM data for a specific purpose. Together with MapAction we are currently working on an OSM Confidence Index within OQT, which should support MapAction’s understanding of the quality of the data behind their core humanitarian map products. Throughout their responses to humanitarian crises, MapAction frequently produces maps within which OSM is a key ingredient. While MapAction teams commonly engage with questions of data quality, they need tools that will support systematic data quality evaluation given the definition of an explicit set of quality requirements. Using the OQT framework, we’re developing Confidence Indices that will help us to answer the following kind of questions:

  • How suitable is the settlement layer from OSM for creating a Malawi country overview map?
  • In which countries is the OSM road network of insufficient quality for creating logistics and transportation maps?

The answers to these questions will inform critical data preparedness activities in countries with humanitarian need.

The OQT has a layered structure: the client-side consisting of a website and the backend-side consisting of different python modules, together with a PostgreSQL GeoDB. The data analyses performed by OQT are powered by the ohsome OpenStreetMap history data analytics platform, which itself consists of different software modules: Specifically the OSHDB, which allows for high-performance data analysis of the OSM history data set, and the ohsome API, which makes these statistics available through a web API.

Authors and Affiliations

Benjamin Herfort (1)
Hannah Ker (2)
Martin Raifer (1)

(1) HeiGIT
(2) MapAction


Use cases & applications


FOSS4G implementations in strategic application domains: land management, crisis/disaster response, smart cities, population mapping, climate change, ocean and marine monitoring, etc.


2 - Basic. General basic knowledge is required.

Language of the Presentation


Benjamin Herfort is researcher at HeiGIT and doctoral candidate in Geography at Heidelberg University. In his research and work he is dealing with OpenStreetMap, MapSwipe and information from social media. He is developing open source tools and methods that incorporate geographic information systems for disaster management and humanitarian aid.

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