VEO: an Ontology for CO2 Emissions from Vehicles

Abstract

The Linked Data best practices provide ways for easier data representation, while at the same time raise the quality of the information that comes with it. The idea behind these best practices is to interlink datasets from various sources which are distributed over different locations and publish the data in an open, machine-readable format so that it would be easier to retrieve and process it by software agents, thus providing opportunities that many new use-cases can be created, which otherwise would not be possible in isolated datasets. With this, the value of the data itself rises to a whole new level. Environmental care is one of the most important issues on a global level, which means that great effort and resources are being spent, to help researchers find new and innovative ways of preserving our world and also to raise awareness of the problem itself. CO2 emissions from vehicles became a large problem in the past few decades, since the number of vehicles exponentially increases, and also people are becoming more mobile than ever, having to commute and travel on a regular basis. In this paper, we describe the process of transformation one-, two- and three-star data about CO2 emissions from vehicles published by the European Environment Agency and various other sources, into five-star Linked Open Data. In addition to that, we developed the Vehicle Emissions Ontology (VEO) to be able to describe the transformed data. We also provide use-case scenarios to show the benefits of using the Linked Data and Open Data concepts in these fields, and provide a public SPARQL endpoint as an entry point for accessing and using the data.