Ontologies of big data, machine learning, and artificial intelligence on the digital railroad

Varvara Lazutkina, Alexander Klimov, Vasily Kupriyanovsky, Dmitry Namiot, Oleg Pokusaev

Abstract


This article focuses on the use of ontologies in digital railway projects. An ontology is a systematic classification of subject knowledge that supports the use of various databases in a meaningful way. Rail transportation has become an area in which productivity is increasingly dependent on the ability to extract information from complex data sets, as well as make optimal decisions in real time. Therefore, effective information and data management are vital for a railway, which is a closely related ontological system of systems where changes in any part can have significant consequences elsewhere. For example, ontology is one of the important factors for implementing a big data risk analysis project (BDRA) for railways. BDRA's goal is to support risk analysis and safety decisions from a wide range of data sources, as well as to improve rail safety risk management. As an example, the work considers ontological design for the digital railway project Rail Baltica. The large role of artificial intelligence and machine learning-based systems is noted. The paper also shows that in order to fully utilize these new technologies, the railway industry must reconsider its approach to collecting and storing data and choosing the right set of ontologies.


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References


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