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Shared Mobility Dashboard for Cologne


Shared Mobility Dashboard for Cologne

KUDOS (Kölner Urbanes Daten Ökosystem, Cologne Urban Data Ecosystem in English) is a collaborative project in which the city of Cologne and the Cologne municipal utility group are working on the implementation of a cross-group data infrastructure, including the necessary strategic and operational alignments. Based on a micro-mobility dashboard protype, the project aims to show how data from different municipal areas can be merged and used to created new synergies. The basic idea of implementingdata synthesis prototypes is to optimize the control and provision of micro-mobility offers on the basis of coherent criteria.


  •  Learning what is important in dealing with urban data.
  • Learning the challenges that exist with regard to compoments of different infrastructure.
  • Key findings about the city's shared mobility offerings (KVB bikes, RhingoRoller).
  • Testing how concepts developed in advance can be implemented using the infrastructure components provided.
  • Demonstrating the advantages and synergies of a Cologne ecosystem for urban data.
  • Opportunities to optimize the service and thus increase customer satisfaction.
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Adaptation for your city

  • This application can be easily obtained through the Urban Data Community.
  • Implementation time: 3 to 6 months
  • On the part of the city, a project owner should be appointed who defines any deviating requirements and accepts development steps.

Necessary technology

  •  Connectors to data sharing platforms and good documentation of API interfaces.
  • Apache Spark modules for processing large amounts of data (Big Data).
  • NoSQL databases like Elastic Search, as more memory is needed for historical analysis.
  • Grafana for data visualization (including Leaflet plug-in).

Factor money

  • A 1:1 The application can be adapted for use in different locations with little effort.
  • UDC members with an open urban data platform can expect about 10 - 35 days of effort.
  • The investment includes the connection of different data sets, the calculation logic (data model) and the visualization of the data in a dashboard.
  • The largest cost factor is the connection of the data.

Lessons Learned

The project and the KUDOS Cologne team have brought many exciting insights, some of which we have summarized here:  

  • Due to the type and form of the data provided, it makes sense to run calculations of the required information using one’s own Big Data applications. In any case, a cost-benefit correlation must be considered in advance. 

  • The definition of criteria for evaluating location positions is simple, but their technical implementation is complex due to possible limiting technical factors.

  • For this use case, historical analyses are particularly relevant. However, in order to make relevant analyses, data must first be collected and stored.

  • Open data visualization tools such as Grafana have many options for display. However, the tool is not designed for geodata or maps in particular. An integration of Leaflet as in the current MVP closes this gap. In the future, other tools such as could be used for this purpose. 

Which SDGS are addressed?

In order to create globally sustainable structures, the member states of the United Nations have set themselves 17 goals by 2030, which are set out in the 2030 Agenda for Sustainable Development.

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The source code of this implementation is available for free adaptation for members of the Urban Data Community. As a member, you can access the Urban Data Community's shared GitHub repository directly by clicking the button. If you have any trouble accessing the code, please contact us.

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Further information

You need support to establish a realization for your city? You would like to know what you have to consider? You would like to adopt the realization, but are not yet a core member of the Urban Data Community (UDC)? Contact the respective experts. We will be happy to assist you!

To UDC Membership
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Verena Mutz

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