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CLEVER: A Framework for Connecting Lived Experiences with Visualisation of Electronic Records

Elshehaly, M., Eddy, L. & Mon-Williams, M. (2023). CLEVER: A Framework for Connecting Lived Experiences with Visualisation of Electronic Records. In: 2023 IEEE Visualization and Visual Analytics (VIS). IEEE VIS: Visualization & Visual Analytics, 22-27 Oct 2023, Melbourne, Australia. doi: 10.1109/VIS54172.2023.00034


The disconnect between insights generated from data and real-life practices of decision makers presents a number of open questions for visual analytics (VA). In public service planning, routine data are often perceived as unavailable, biased, incomplete and inconsistent across services. Decision makers often rely on qualitative data - sometimes collected through co-production - to understand the lived experience of communities before formulating a decision. We followed a subjectivist case study approach and immersed ourselves in ongoing co-production activities over the course of one year, to capture how VA can support the dialogue between population health decision-makers and the communities they serve. We present a framework for Connecting Lived Experiences with Visualisation of Electronic Records (CLEVER). The framework regards visualisation as a central component in a complex adaptive decision-making ecosystem and highlights the need to structure domain knowledge across decision contexts in Population Health Management (PHM) at clinical-, service- and district-levels. Our process for developing an initial framework comprised three steps: (i) we elicited decisionmaking tasks through a series of qualitative data collection activities; (ii) we developed a preliminary domain model to capture data views and a subjective view of the world through human stories; and (iii) we developed a series of visualisation prototypes to instantiate the framework and demonstrated them regularly to stakeholders. In future work, we will conduct ‘deep dives’ to systematically study the role of VA in individual stages of the framework.

Publication Type: Conference or Workshop Item (Paper)
Additional Information: © 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Publisher Keywords: Human-centered computing, Visualization, Visualization design and evaluation methods
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine
Departments: School of Science & Technology > Computer Science
[thumbnail of CLEVER_Short_Paper_VIS_2023.pdf]
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