A big data modeling approach with graph databases for SPAD risk
- Submitting institution
-
The University of Huddersfield
- Unit of assessment
- 12 - Engineering
- Output identifier
- 2
- Type
- D - Journal article
- DOI
-
10.1016/j.ssci.2017.11.019
- Title of journal
- Safety Science
- Article number
- -
- First page
- 75
- Volume
- 110
- Issue
- Part B
- ISSN
- 0925-7535
- Open access status
- Access exception
- Month of publication
- December
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
4
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work proposes a novel approach based on big data techniques to show transformative potential of gaining more understanding about the performance and safety of train movments using day to day real life data. The results of the research were well received from the industry comnuity and the developed model is receiving further industrial funding via the strategic partnership between the university of Huddersfield and The Rail Safety and Standards Board (RSSB), to enhance risk assessment using an augmented BowTie. This paper was published in Q1 journal.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
