The Data Sandbox+ research competition builds on the success of the original ‘Data Sandbox’ initiative that RSSB launched in 2017. This funded five feasibility studies on how data can be used in novel ways to support performance improvements.

Through the Data Sandbox+, which RSSB is funding in collaboration with Network Rail’s R&D programme, we are making £1.3m available to fund demonstrator projects. These will build on the work that has already been carried out, or on feasibility studies which propose new approaches and ideas.

Proposals are invited for innovative data-driven solutions to these key operational performance challenges:

  • predicting and minimising reactionary delays
  • understanding train movements
  • reducing dwell time variations
  • management of disruptions
  • better measuring and understanding performance and delays
  • other challenges, as identified by relevant owners (such as Network Rail or passenger and freight operators).

Data Sandbox+ builds on the repository of data that was made available for the original competition and includes new and refreshed content. If you would like to get involved by sharing data samples to enhance the repository and support future research, please get in touch.

The first round of the competition led to the funding of three demonstrator projects and one feasibility study, which started in November 2019:

  • “Real time prediction and mitigation of disruption through personalised passenger communications”, led by Zipabout and the University of Birmingham, in collaboration with LNER.
  • “Rail performance modelling for strategic decision making”, led by Risk Solutions, in collaboration with City University, Heriott-Watt University, University of Southampton, Steer and Tracsis.
  • “IntelliDwell”, led by Porterbrook in collaboration with ScotRail, University of Southampton and Elastacloud.
  • “Data-driven robust timetabling”, led by the University of Southampton, in collaboration with Network Rail and Bellvedi/Tracsis.

The second round of the competition closed on 6 December 2019. These three projects have since been announced and are due to get underway shortly:

  • “Utilising deep analytics to predict reactionary delays and dwell time variation in the new accessible railway” led by Transreport in collaboration with RDG and GWR.
  • “A Real-Time Functional Digital Twin for the Thameslink Route”, led by Open Space in collaboration with the University of Birmingham, Network Rail, RDG and GWR.
  • “Rapid Evaluation and Planning Analysis Infrastructure for Railways (REPAIR)” led by Fraser Nash in collaboration with the University of Hull.

For more information about the competition visit the Data Sandbox+ hub or contact