Selected contributions from the Open Source Software Certification (OpenCert) workshops

We present to you this special issue dedicated to the 2nd, 3rd and 4th editions of the International Workshop on Foundations and Techniques for Open Source Software Certification (OpenCert) held in 2008 (Milan, Italy), 2009 (York, UK) and 2010 (Pisa, Italy) respectively. This is a compilation of a selected set of extended papers presented at these workshops. OpenCert provides for a unique venue advancing the state of the art in the analysis and assurance of open source software with an ultimate aim of achieving certification and standards. The dramatic growth in open source software over recent years has provided for a fertile ground for fundamental research and demonstrative case studies. Over the years, OpenCert has enabled a thriving community, small but focused, examining issues ranging from certification to security and safety analysis for applications areas as diverse as railways, aviation, knowledge management, sustainable development, and the open source developers community

Towards a knowledge-based approach for effective decision making in railway safety

Purpose – This paper aims to contribute towards understanding how safety knowledge can be elicited from railway experts for the purposes of supporting effective decision-making. Design/methodology/approach – A consortium of safety experts from across the British railway industry is formed. Collaborative modelling of the knowledge domain is used as an approach to the elicitation of safety knowledge from experts. From this, a series of knowledge models is derived to inform decision-making. This is achieved by using Bayesian networks as a knowledge modelling scheme, underpinning a Safety Prognosis tool to serve meaningful prognostics information and visualise such information to predict safety violations. Findings – Collaborative modelling of safety-critical knowledge is a valid approach to knowledge elicitation and its sharing across the railway industry. This approach overcomes some of the key limitations of existing approaches to knowledge elicitation. Such models become an effective tool for prediction of safety cases by using railway data. This is demonstrated using passenger–train interaction safety data. Practical implications – This study contributes to practice in two main directions: by documenting an effective approach to knowledge elicitation and knowledge sharing, while also helping the transport industry to understand safety. Social implications – By supporting the railway industry in their efforts to understand safety, this research has the potential to benefit railway passengers, staff and communities in general, which is a priority for the transport sector. Originality/value – This research applies a knowledge elicitation approach to understanding safety based on collaborative modelling, which is a novel approach in the context of transport. </jats:sec