Dr John Easton MEng, PhD, MCMI, MIET, MIEEE

John Easton

Department of Electronic, Electrical and Systems Engineering
Lecturer

Contact details

Telephone
+44 (0) 121 414 4315
Email
j.m.easton@bham.ac.uk
View my research portal
Address
School of Electronic, Electrical and Systems Engineering
University of Birmingham
Edgbaston
Birmingham
B15 2TT
UK

Dr John Easton is a Lecturer working with the Birmingham Centre for Railway Research and Education at the University of Birmingham. His research interests centre on methods for the storage, processing and display of railway related datasets – in particular data representation and exchange via ontologies, manipulation and integration of data relevant to the multimodal transport system, and cyber security in industrial control systems.

Qualifications

  • PhD in “Optimised analysis and visualisation of metabolic data using graph theoretical approaches”, University of Birmingham (2009)
  • MEng (Hons) in Computer Systems Engineering with Management, University of Birmingham (2004)
  • Member of the Institute of Electrical and Electronics Engineers (IEEE)
  • Member of the Institute of Engineering and Technology (IET)
  • Member of the Chartered Management Institute (CMI)

Biography

Initially working in the field of Metabolomics, where he developed data models for the exchange and analysis of NMR data, John moved to the Birmingham Centre for Railway Research and Education in 2009. Since then he’s worked on a range of data driven projects in rail, and currently leads the research activity on data integration, management and cyber security for the UK Rail Research and Innovation Network’s (UKRRIN) Centre of Excellence in Digital Systems. John is actively involved in hosting conferences in the area of transportation data, acting as the programme chair of the Institution of Engineering and Technology (IET) International Conference on Railway Engineering’s European events, and chairing an annual workshop at the IEEE’s Big Data conferences in the USA.

Alongside his academic duties, John sits on the GB rail industry’s Data and Information Systems Interface Committee (DISIC), and is the Chair of the IET Railway Technical and Professional Network.

Postgraduate supervision

John Easton's research interests centre on methods for the storage, processing and display of railway related datasets - in particular data representation and exchange via ontologies, manipulation and integration of data relevant to the multimodal transport system, and cyber security in industrial control systems.

Research

Methods for the storage, processing and display of railway related datasets; in particular data representation and exchange via ontologies, manipulation and integration of data relevant to the multimodal transport system, and cyber security in industrial control systems.

Other activities

Member of the IET Railway Technical and Professional Network (TPN) Executive Team – January 2015 to present.

Publications

Recent publications

Book

Kohli, S, Senthil Kumar, AV, Easton, J & Roberts, C (eds) 2017, Innovative Applications of Big Data in the Railway Industry. IGI Global. https://doi.org/10.4018/978-1-5225-3176-0

Article

Fu, Q & Easton, J 2018, 'Prediction of weather-related incidents on the rail network: prototype data model for wind-related delays in Great Britain', ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, vol. 4, no. 3, 04018027. https://doi.org/10.1061/AJRUA6.0000975

Schober, D, Jacob, D, Wilson, M, Cruz, JA, Marcu, A, Grant, JR, Moing, A, Deborde, C, De Figueiredo, LF, Haug, K, Rocca-Serra, P, Easton, J, Ebbels, TMD, Hao, J, Ludwig, C, Günther, UL, Rosato, A, Klein, MS, Lewis, IA, Luchinat, C, Jones, AR, Grauslys, A, Larralde, M, Yokochi, M, Kobayashi, N, Porzel, A, Griffin, JL, Viant, MR, Wishart, DS, Steinbeck, C, Salek, RM & Neumann, S 2018, 'nmrML: A Community Supported Open Data Standard for the Description, Storage, and Exchange of NMR Data', Analytical Chemistry, vol. 90, no. 1, pp. 649-656. https://doi.org/10.1021/acs.analchem.7b02795

Easton, J & Kohli, S 2017, 'Challenges and opportunities for big data in the digital railway' Rail Technology Magazine, pp. 38. <http://www.railtechnologymagazine.com/Comment/challenges-and-opportunities-for-big-data-in-the-digital-railway>

Tutcher, J, Easton, J & Roberts, C 2017, 'Enabling Data Integration in the Rail Industry Using RDF and OWL - the RaCoOn Ontology', ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, vol. 3, no. 2. https://doi.org/10.1061/AJRUA6.0000859

Chapter

Easton, J 2017, Blockchains: A Distributed Data Ledger for the Rail Industry. in S Kohli, AV Senthil Kumar, J Easton & C Roberts (eds), Innovative Applications of Big Data in the Railway Industry. IGI Global, pp. 27-39. https://doi.org/10.4018/978-1-5225-3176-0.ch002

Conference contribution

Alzahrani, R, Herko, S & Easton, J 2020, Blockchain Application in Remote Condition Monitoring. in 2020 IEEE International Conference on Big Data (Big Data). 2020 IEEE International Conference on Big Data (Big Data), 10/12/20.

Preece, J & Easton, J 2020, Blockchain technology as a mechanism for digital railway ticketing. in 2019 IEEE International Conference on Big Data (Big Data). IEEE Xplore, pp. 3599-3606, 2019 IEEE International Conference on Big Data (Big Data), Los Angeles, United States, 9/12/19. https://doi.org/10.1109/BigData47090.2019.9006293

Armstrong, J, Rempelos, G, Wei, J, Preston, J, Blainey, S, Easton, J & Roberts, C 2020, DEVELOPING A GENERALISED ASSESSMENT FRAMEWORK FOR RAILWAY INTERVENTIONS. in G Passerini, JM Mera & R Takagi (eds), Computers in Railways XVII: Proceedings of the 17th International Conference on Railway Engineering Design and Operation (COMPRAIL 2020). WIT Transactions on the Built Environment, vol. 199, WIT Press, pp. 127-138. https://doi.org/10.2495/CR200121

Jaroszweski, D, Fu, Q & Easton, J 2019, A data model for heat-related rail buckling: implications for operations, maintenance and long-term adaptation. in Proceedings of the 12th World Congress on Railway Research. World Congress on Railway Research, Tokyo, Japan, 28/10/19.

Preece, J & Easton, J 2019, Towards encrypting industrial data on public distributed networks. in 2018 IEEE International Conference on Big Data (Big Data)., 8622246, IEEE Press / Wiley, pp. 4540-4544, 2018 IEEE International Conference on Big Data (Big Data), Seattle, United States, 10/12/18. https://doi.org/10.1109/BigData.2018.8622246

Fu, Q, Jaroszweski, D & Easton, J 2018, A prototype model for understanding heat-related rail incidents: a case study on the Anglia area in Great Britain. in Proceedings of the 8th International Conference on Railway Engineering (ICRE 2018). Institution of Engineering and Technology, 8th International Conference on Railway Engineering (ICRE 2018), London, United Kingdom, 16/05/18. https://doi.org/10.1049/cp.2018.0071

Fu, Q & Easton, J 2018, Understanding data quality: ensuring data quality by design in the rail industry. in Proceedings of the 2017 IEEE International Conference on Big Data (BIGDATA). IEEE Xplore, pp. 3792-3799, 2017 IEEE International Conference on Big Data, Boston, United States, 11/12/17. https://doi.org/10.1109/BigData.2017.8258380

Morris, C & Easton, J 2018, Use of ontology for data integration in a degraded mode signalling system. in G Passerini, J M. Mera, N Tomii & P Tzieropoulos (eds), Computers in Railways XVI. WIT Transactions on The Built Environment, vol. 181, WIT Press, pp. 215-223, 16th International Conference on Railway Engineering Design & Operation (COMPRAIL 2018)
, Lisbon, Portugal, 2/07/18. https://doi.org/10.2495/CR180191

Paper

Fu, Q & Easton, J 2018, 'A data model for prediction of weather-related rail incidents: a case-study example of wind-related incidents on the rail network in Great Britain', Paper presented at 50th Annual Conference of the Universities’ Transport Study Group, London, United Kingdom, 3/01/18 - 5/01/18.

View all publications in research portal