ChargingPoints Exploration

Introduction

For the University of Twente Smart Industry Systems course project we have explored the possibility of including data upon Charging Points into the Kadaster knowledge graph. The idea behind this is to make the Charging Points data FAIR in order to hopefully overcome limitations that come with the electrical net and other problems that increasing the amount of charging stations might bring. In order to do this we have developed a model to fit all - we think - necessary data.

View of model

View of data available for Amsterdam/Rotterdam/Utrecht

Method

To proof that federating this data and linking it to the Kadaster knowledge graph could be useful, we have collected some data upon Amsterdam's charging points using the API behind their web viewer and converted this to linked data.

Determining the spread of charging points

A fairly easy application, which does not necessarily need a link to Kadaster, but could be useful to see as federated data -rather than from one municipality in particular - to determine "coverage" nation wide is a heat map consisting of charging points. Below is an example of such a heat map for some charging points collected using the Amsterdam API.

Surroundings

Further applications could be for the municipalities or other parties to see at which locations charging points are placed. Below is shown that it is possible to determine the buildings at the same address of the charging points and their functions. This way it could be able to determine whether a charging point is placed at a residential building, office building, industrial building or perhaps even a sporting facility or other types of buildings.

Per Gemeente

Lastly, by linking it to a place we can also trace back in which Municipality(/Gemeente) a charging point is placed. This gives us with the following distribution for the inserted data.

Charging point property display

Finally, the properties of the ChargingPoints can also be retrieved and shown accordingly. Providing the end-user with information on each ChargingPoint without needing other resources or specific knowledge on how to query using SparQL. This brings the data retrieval back around to also supporting the current implementation with respect to Charging Points many municipalities offer, namely a map to see each charging point with some respective attributes. Since our model would contain respectively more properties per Charging Points than Amsterdam, Utrecht or Rotterdam currently offer, a full and proper implementation of this view could be a good contender. It also has the benefit that this dataset would be nation wide and there can be one centralized view instead of being limited to the borders of a specific municipality.