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Blay_Information Resilience Framework (IRF).pdf (1.3 MB)

The information resilience framework: Vulnerabilities, capabilities and requirements.

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journal contribution
posted on 2020-04-24, 14:48 authored by Karen BlayKaren Blay, Steven Yeomans, Peter DemianPeter Demian, Danny Murguia

The quality of information is crucial to the success of asset delivery, management and performance in the Digitised Architecture, Engineering, Construction and Operations (DAECO) sector. The exposure and sensitivity of DAECO information to threats during its lifecycle leaves it vulnerable, affecting the intrinsic, relational and security dimensions of information quality. A resilient information lifecycle perspective which identifies capabilities and requirements is therefore needed to assure information quality amid threats. This research develops and presents an information resilience (IR) framework by drawing on the theories of resilience, information quality and vulnerability. In developing the framework, the critical incident technique was employed in interviewing 30 professionals (average of 40-minutes) in addition to reviewing 7 project-documents across three digitally-driven infrastructure projects (making up 324-pages of data). The validated capabilities and requirements identified from this study have been collated into the framework and this highlight the need for cognitive-driven capabilities and process-driven requirements in DAECO.

Funding

Centre for Digital Built Britain, under InnovateUK grant number RG96233

History

School

  • Architecture, Building and Civil Engineering

Published in

Journal of Data and Information Quality

Volume

12

Issue

3

Pages

14

Publisher

Association for Computing Machinery (ACM)

Version

  • AM (Accepted Manuscript)

Rights holder

© ACM

Publisher statement

"© {Owner/Author | ACM} {Year}. This is the author's version of the work. It is posted here under a cc by-nc-nd license with permission of the publisher. The definitive Version of Record was published in Journal of Data and Information Quality,12(3): 14. https://doi.org/10.1145/3388786

Acceptance date

2020-03-16

Publication date

2020-07-27

Copyright date

2020

ISSN

1936-1955

Language

  • en

Depositor

Dr Karen Blay Deposit date: 21 April 2020

Article number

14

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