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dc.contributor.authorAjayi, Oluwafemien_US
dc.contributor.authorSinnott, Richard O.en_US
dc.contributor.authorSTELL, ANTHONYen_US
dc.contributor.authorYoung, Alanen_US
dc.date.accessioned2014-05-21T22:09:07Z
dc.date.available2014-05-21T22:09:07Z
dc.date.issued2008en_US
dc.identifier.citationAjayi, O., Sinnott, R. O., Stell, A., & Young, A. (2008). Blind data aggregation from distributed, protected sources. In UK e-Science All Hands Meeting, Edinburgh, UK.en_US
dc.identifier.urihttp://hdl.handle.net/11343/28849
dc.descriptionThis is a pre-print of a paper from UK e-Science All Hands Meeting 2008. http://www.allhands.org.uk/2008/index.htmlen_US
dc.description.abstractSuccessful e-health research depends on access to and usage of a wide range of clinical, biomedical, social, geo-spatial, environmental and other data sets. In large scale, multi-centre clinical studies crossing geographical and organizational divides, the need to access, link and aggregate data securely is essential. Whilst the e-Science community have come up with a wide variety of technologies that support authentication and authorization, past experiences from working with organizations such as the National Health Service (NHS) in projects such as the MRC funded Virtual Organizations for Trials and Epidemiological Studies (VOTES) project, have shown that irrespective of the technological advances and capabilities offered by the e-Science community, data providers themselves are typically unwilling to provide direct access to their data sets, i.e. through penetration of the NHS firewall for example from HE/FE. There are many reasons for this which we outline in this paper, both pragmatic and technological. Ultimately, data providers and the key stakeholders in this space are acutely aware of confidentiality and ethics concerns on data access and usage. They will only release their data provided it can be ensured that it is not possible to link it with other data sets that can result in potential violations of patient confidentiality for example through statistical disclosure. This paper presents a novel approach and its implementation that directly addresses these issues, providing a so-called Virtual Anonymisation Grid for Unified Access to Remote Clinical Data (Vanguard). Key features of Vanguard are its support for pull models of interaction with data providers such as the NHS, who do not necessarily have to open up their firewalls and thereby open themselves up to risks of attack; support of secure, anonymous data aggregation; support for novel ways in which data release to users undertaking research allows them to obtain and use data in a secure, disclosure free environment where third parties cannot access/use any released data. We demonstrate this through case studies applying the Vanguard system to clinical scenarios and systems working with the NHS in Scotland.en_US
dc.languageengen_US
dc.publisherNational e-Science Centre, University of Glasgowen_US
dc.subjecte-health researchen_US
dc.subjectdata setsen_US
dc.subjectdata accessen_US
dc.subjectclinical studiesen_US
dc.subjectconfidentialityen_US
dc.subjectethicsen_US
dc.subjectVanguard systemen_US
dc.titleBlind data aggregation from distributed, protected sourcesen_US
dc.typeConference Paperen_US
melbourne.peerreviewPeer Revieweden_US
melbourne.affiliationThe University of Melbourneen_US
melbourne.affiliation.departmentComputing and Information Systems
melbourne.affiliation.facultyEngineering and Information Technology
melbourne.publication.statusPublisheden_US
melbourne.source.titleUK e-Science All Hands Meetingen_US
melbourne.source.locationconferenceEdinburgh, UKen_US
dc.description.sourcedateconference8-11 Septemberen_US
melbourne.elementsidNA
melbourne.contributor.authorSinnott, Richard
melbourne.contributor.authorStell, Anthony
melbourne.accessrightsOpen Access


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