Modeling views in the layered view model for XML using UML

In data engineering, view formalisms are used to provide flexibility to users and user applications by allowing them to extract and elaborate data from the stored data sources. Conversely, since the introduction of Extensible Markup Language (XML), it is fast emerging as the dominant standard for storing, describing, and interchanging data among various web and heterogeneous data sources. In combination with XML Schema, XML provides rich facilities for defining and constraining user-defined data semantics and properties, a feature that is unique to XML. In this context, it is interesting to investigate traditional database features, such as view models and view design techniques for XML. However, traditional view formalisms are strongly coupled to the data language and its syntax, thus it proves to be a difficult task to support views in the case of semi-structured data models. Therefore, in this paper we propose a Layered View Model (LVM) for XML with conceptual and schemata extensions. Here our work is three-fold; first we propose an approach to separate the implementation and conceptual aspects of the views that provides a clear separation of concerns, thus, allowing analysis and design of views to be separated from their implementation. Secondly, we define representations to express and construct these views at the conceptual level. Thirdly, we define a view transformation methodology for XML views in the LVM, which carries out automated transformation to a view schema and a view query expression in an appropriate query language. Also, to validate and apply the LVM concepts, methods and transformations developed, we propose a view-driven application development framework with the flexibility to develop web and database applications for XML, at varying levels of abstraction

Data integration for offshore decommissioning waste management

Offshore decommissioning represents significant business opportunities for oil and gas service companies. However, for owners of offshore assets and regulators, it is a liability because of the associated costs. One way of mitigating decommissioning costs is through the sales and reuse of decommissioned items. To achieve this effectively, reliability assessment of decommissioned items is required. Such an assessment relies on data collected on the various items over the lifecycle of an engineering asset. Considering that offshore platforms have a design life of about 25 years and data management techniques and tools are constantly evolving, data captured about items to be decommissioned will be in varying forms. In addition, considering the many stakeholders involved with a facility over its lifecycle, information representation of the items will have variations. These challenges make data integration difficult. As a result, this research developed a data integration framework that makes use of Semantic Web technologies and ISO 15926 - a standard for process plant data integration - for rapid assessment of decommissioned items. The proposed solution helps in determining the reuse potential of decommissioned items, which can save on cost and benefit the environment