This paper presents early findings from a larger study, into the use of linked data in the rail domain. The study and other literature has shown there to be benefits from improved integration of data in this domain and proposes that linked data in general and ontology in particular will address this. The paper will set out the current state of data integration in the British rail domain, highlighting issues found there. The manner in which linked data is employed in the broader transport domain will then be examined along with previous work pertaining to the rail domain.
This paper presents the railway core ontologies, a group of related ontologies designed to model the rail domain in detail. The purpose of these ontologies is to enable improved data integration in the rail domain, which will deliver business benefits in the form of improved customer perceptions and more efficient use of the rail network. The modularity of the ontologies allows for both detailed modelling of the domain at a high level and the storing of instance data at lower levels. It concludes that the benefits of improved rail data integration are best realised through the use of the railway core ontologies.Presented at KEOD 2015
This paper puts forward the case for using RaCoOn for data integration in the the rail domain and sets out tools for expanding RaCoOn
Every week many thousands of delay minutes are accrued on the UK railway, a significant proportion of which can be attributed to failures of signalling sub-systems, such as track circuits. Signalling failures are both expensive for the infrastructure provider (as knock-on delays to services build up rapidly) and a source of frustration and delays for passengers, leading to increased dissatisfaction with the industry as a whole. A degraded mode signalling system, offering less functionality than the main system but via alternative channels, can help to mitigate these failures and allow railway operations to continue whilst the main signalling system is repaired. The use of ontology was a key enabler in this project, making it possible to draw together data from multiple sources and infer meaning from the data supplied. National scale signalling data was used with the ontology without impediment
This was presented at: Comprail 2018
The exchange of information is crucial to the operation of railways; starting with the distribution of timetables, information must constantly be exchanged in any railway network. The slow evolution of the information environment within the rail industry has resulted in the existence of a diverse range of systems, only able to exchange information essential to railway operations. Were the cost of data integration reduced, then further cost reductions and improvements to customer service would follow as barriers to the adoption of other technologies are removed.
The need for data integration has already been studied extensively and has been included in the UK industry's rail technical strategy, however, despite it's identification as a key technique for improving integration, uptake of ontology remains limited. This thesis considers techniques to reduce barriers to the take up of ontology in the UK rail industry, and presents a case study in which these techniques are applied. Amongst the key barriers to uptake identified are a lack of software engineers with ontology experience, and the diverse information environment within the rail domain. Techniques to overcomes these barriers using software based tools are considered, and example tools produced which aid the overcoming of these barriers.
The case study presented is of a degraded mode signalling system, drawing data from many sources, made more flexible in it's select of the available datasources by use of ontology. Tools created to improve data integration are employed in this commercial project, successfully combing signalling data with (simulated) train positioning data.
This was a thesis submitted to the University of Birmingham for the degree of Doctor of Philosophy.
If you wish to how it was made you can, via github