One reason oil and gas companies adopt a standard cost coding system is to facilitate benchmarking. NORSOK Z-014 Standard Cost Coding System (SCCS) is an example of this kind of system. This paper describes a set of issues found in a project that attempted to adopt this standard. These were issues whose analysis revealed problems with the standard’s fundamental structure. Further analysis showed that these types of problems are well understood outside the project controls community and resolvable using a classification technique technically known as ‘facets’. The paper provides examples of these issues and indicates how they can be resolved. It also describes the systematic modernization approach adopted by the project to resolve the issues throughout the standard. The aim of this paper is to introduce to the project controls community an understanding of the importance of these issues for raising the quality of their data and the new techniques to provide improved foundations for standard cost coding systems for the oil and gas industry in the 21st Century.

In common with many other government defence departments, the UK Ministry of Defence (MoD) has realised that it has a plethora of legacy systems that were procured as domain specific with little emphasis given to integration requirements. In particular, it realised that the lack of integration between a significant number of the legacy air defence command and control (AD-C2) systems meant it could not deliver the increased agility needed for joint force AD and that current approaches to integration were unlikely to resolve the problem. They realised that they needed a new approach that demonstrably worked. This paper describes a programme initiated by the MoD to address this problem through the formulation of a novel solution and its demonstration in the tactical AD-C2 environment using a sample of these existing legacy systems. It describes the ontological solution deployed to resolve the 'hard' semantic interoperability challenge. It outlines the physical and semantic architecture that was developed to support this approach and describes the implemented planning and collaborative execution (PACE-based) and semantic interoperability engine (SIE) solution.