Zou, Mengsong, Diaz-Montes, Javier, Rodero, Ivan, Parashar, Manish, Petri, Ioan ORCID: https://orcid.org/0000-0002-1625-8247, Rana, Omer Farooq ORCID: https://orcid.org/0000-0003-3597-2646, Qi, Xin and Foran, David J. 2014. Collaborative marketplaces for eScience: A medical imaging use case. Presented at: 2014 International Conference on Collaboration Technologies and Systems (CTS), 19-23 May 2014, Minneapolis, MN, USA. Collaboration Technologies and Systems (CTS), 2014 International Conference on. pp. 500-506. 10.1109/CTS.2014.6867615 |
Abstract
The development of digital imaging technology is creating extraordinary levels of accuracy that provide support for improved reliability in different aspects of the image analysis such as content-based image retrieval, image segmentation and classification. This has dramatically increased the volume and generation rates of data, which make querying and sharing non-trivial, and render centralized solutions infeasible. Moreover, in many cases this data is naturally distributed or has to be shared across multiple institutions requiring decentralized solutions. In this paper, we present a federation approach that can take advantage of advanced cyber-infrastructure (ACI) by seamlessly and securely interacting with information/data located across geographically distributed resources. We describe and evaluate the establishment of a federated marketplace across resources from UK and US in the context of collaborative research in medical imaging. We show how users from different sites can transparently access to remote data by placing computational requests in the marketplace. Moreover, we evaluate different pricing policies to demonstrate how site providers and users can benefit from such federation.
Item Type: | Conference or Workshop Item (Paper) |
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Date Type: | Publication |
Status: | Published |
Schools: | Engineering Computer Science & Informatics |
Subjects: | Q Science > Q Science (General) Q Science > QA Mathematics > QA76 Computer software R Medicine > R Medicine (General) |
Last Modified: | 27 Oct 2022 09:32 |
URI: | https://orca.cardiff.ac.uk/id/eprint/66274 |
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