The grid: blueprint for a new computing infrastructure
The grid: blueprint for a new computing infrastructure
Extracting Business Benefit from Operational Data
HPCN Europe 2000 Proceedings of the 8th International Conference on High-Performance Computing and Networking
The design and implementation of Grid database services in OGSA-DAI: Research Articles
Concurrency and Computation: Practice & Experience - Grid Performance
The Anatomy of the Grid: Enabling Scalable Virtual Organizations
International Journal of High Performance Computing Applications
Distributed Computing Economics
Queue - Object-Relational Mapping
Grid and Cloud Computing: A Business Perspective on Technology and Applications
Grid and Cloud Computing: A Business Perspective on Technology and Applications
Runtime measurements in the cloud: observing, analyzing, and reducing variance
Proceedings of the VLDB Endowment
Intercontinental Grids: An Infrastructure for Demand-Driven Innovation
Journal of Grid Computing
On the Performance Variability of Production Cloud Services
CCGRID '11 Proceedings of the 2011 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing
Addressing cloud computing security issues
Future Generation Computer Systems
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There is a wealth of digital data currently being gathered by commercial and private concerns that could supplement academic research. To unlock this data it is important to gain the trust of the companies that hold the data as well as showing them how they may benefit from this research. Part of this trust is gained through established reputation and the other through the technology used to safeguard the data. This paper discusses how different technology frameworks have been applied to safeguard the data and facilitate collaborative work between commercial concerns and academic institutions. The paper focuses on the distinctive requirements of e-Social Science: access to large-scale data on behaviour in society in environments that impose confidentiality constraints on access. These constraints arise from both privacy concerns and the commercial sensitivities of that data. In particular, the paper draws on the experiences of building an intercontinental Grid-INWA-from its first operation connecting Australia and Scotland to its subsequent extension to China across the Trans-Eurasia Information Network-the first large-scale research and education network for the Asia-Pacific region. This allowed commercial data to be analysed by experts that were geographically distributed across the globe. It also provided an entry point for a major Chinese commercial organisation to approve use of a Grid solution in a new collaboration provided the centre of gravity of the data is retained within the jurisdiction of the data owner. We describe why, despite this approval, an embedded solution was eventually adopted. We find that 'data sovereignty' dominates any decision on whether and how to participate in e-Social Science collaborations and how this might impact on a Cloud based solution to this type of collaboration.