scholarly journals The case for IT transformation and big data for safety risk management on the GB railways

2018 ◽  
Vol 232 (2) ◽  
pp. 151-163 ◽  
Author(s):  
Coen van Gulijk ◽  
Peter Hughes ◽  
Miguel Figueres-Esteban ◽  
Rawia El-Rashidy ◽  
George Bearfield
Keyword(s):  
Risk Management ◽  
Big Data ◽  
Data Driven ◽  
Management Systems ◽  
Research Needs ◽  
Safety Risk ◽  
Digital Skills ◽  
Analysis Programme ◽  
Opening Up ◽  
Very High

This article presents the case for IT transformation and big data for safety risk management on the GB railways. This article explains why the interest in data-driven safety solutions is very high in the railways by describing the drivers that shape risk management for the railways. A brief overview of research projects in the big data risk analysis programme supports the case and helps understand the research agenda for the transformation of safety and risk on the GB railways. The drivers and the projects provide insight in the current research needs for the transformation and explains why safety researchers have to broaden their skill set to include digital skills and potentially even programming. The case for IT transformation of risk management systems is compelling, and this article describes just the tip of the iceberg of opportunities opening up for safety analysis that, after all, depends on data.

Towards a Service-Oriented Architecture for Knowledge Management in Big Data Era

2018 ◽  
Vol 14 (4) ◽  
pp. 24-38 ◽  
Author(s):  
Thang Le Dinh ◽  
Thuong-Cang Phan ◽  
Trung Bui ◽  
Manh Chien Vu
Keyword(s):  
Big Data ◽  
Knowledge Management ◽  
Service Oriented Architecture ◽  
Current Knowledge ◽  
Business Environment ◽  
Data Driven ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Service Oriented ◽  
New Generation

Nowadays, big data is a revolution that transforms conventional enterprises into data-driven organizations in which knowledge discovered from big data will be integrated into traditional knowledge to improve decision-making and to facilitate organizational learning. Consequently, a major concern is how to evolve current knowledge management systems, which are confronted with a various and unprecedented amount of data, resulting from different data sources. Therefore, a new generation of knowledge management systems is required for exploring and exploiting big data as well as for facilitating the knowledge co-creation between the society and its business environment to foster innovation. This article proposes a service-oriented architecture for elaborating a new generation of big data-driven knowledge management systems to help enterprises to promote knowledge co-creation and to obtain more business value from big data. The proposed architecture is presented based on the principles of design science research and its evaluation uses the analytical evaluation method.

scholarly journals Rethinking data‐driven decision support in flood risk management for a big data age

2020 ◽  
Vol 13 (4) ◽  
Author(s):  
Ross Towe ◽  
Graham Dean ◽  
Liz Edwards ◽  
Vatsala Nundloll ◽  
Gordon Blair ◽  
...  
Keyword(s):  
Risk Management ◽  
Big Data ◽  
Decision Support ◽  
Flood Risk ◽  
Flood Risk Management ◽  
Data Driven
Sign in / Sign up

Export Citation Format

Share Document