Supporting interoperability frameworks in the UK public sector

This paper describes the design and implementation of a component based software application, which alleviates the problem of software interoperability in the UK public sector. We analyze the current interoperability frameworks across the United Kingdom (UK) and European Union (EU) and propose a software solution that enhances such interoperability initiatives. Our example scenario is placed within a UK local authority, which shares data stored within the Police databases, for making efficient and more accurate operational decisions. The prototype, implemented as a J2EE application and built upon existing databases, proves our concept that it is possible to achieve data and application interoperability without integrating data sources and without using XML formats for data sharing.

Extending Science Gateway Frameworks to Support Big Data Applications in the Cloud

Cloud computing offers massive scalability and elasticity required by many scien-tific and commercial applications. Combining the computational and data handling capabilities of clouds with parallel processing also has the potential to tackle Big Data problems efficiently. Science gateway frameworks and workflow systems enable application developers to implement complex applications and make these available for end-users via simple graphical user interfaces. The integration of such frameworks with Big Data processing tools on the cloud opens new oppor-tunities for application developers. This paper investigates how workflow sys-tems and science gateways can be extended with Big Data processing capabilities. A generic approach based on infrastructure aware workflows is suggested and a proof of concept is implemented based on the WS-PGRADE/gUSE science gateway framework and its integration with the Hadoop parallel data processing solution based on the MapReduce paradigm in the cloud. The provided analysis demonstrates that the methods described to integrate Big Data processing with workflows and science gateways work well in different cloud infrastructures and application scenarios, and can be used to create massively parallel applications for scientific analysis of Big Data.