Incorporating Uncertainty into Decision-Making: An Information Visualisation Approach

Daradkeh, Mohammad; Abul-Huda, Bilal

doi:10.1007/978-3-319-57487-5_6

Cited by 4 publications

(2 citation statements)

References 16 publications

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“…By understanding that point estimates may vary, users can make more informed decisions. This holds especially when working with DSSs [68], so visualising their uncertainty is crucial. However, in agriculture, the application of uncertainty visualisations is limited [9].…”

Section: Uncertainty-aware Price Predictionmentioning

confidence: 99%

Developing Visual-Assisted Decision Support Systems across Diverse Agricultural Use Cases

et al. 2022

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Decision support systems (DSSs) in agriculture are becoming increasingly popular, and have begun adopting visualisations to facilitate insights into complex data. However, DSSs for agriculture are often designed as standalone applications, which limits their flexibility and portability. They also rarely provide interactivity, visualise uncertainty and are evaluated with end-users. To address these gaps, we developed six web-based visual-assisted DSSs for various agricultural use cases, including biological efficacy correlation analysis, water stress and irrigation requirement analysis, product price prediction, etc. We then evaluated our DSSs with domain experts, focusing on usability, workload, acceptance and trust. Results showed that our systems were easy to use and understand, and participants perceived them as highly performant, even though they required a slightly high mental demand, temporal demand and effort. We also published the source code of our proposed systems so that they can be re-used or adapted by the agricultural community.

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Section: Uncertainty-aware Price Predictionmentioning

confidence: 99%

Developing Visual-Assisted Decision Support Systems across Diverse Agricultural Use Cases

et al. 2022

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“…In the field of administration, several case studies demonstrated the effectiveness of the information visualization for reducing uncertainty when analysing financial issues (Daradkeh and Abul-Huda, 2017) or sales transactions of small producers (Hoelscher and Mortimer, 2018).…”

Section: Introductionmentioning

confidence: 99%

Applied bibliometrics and information visualization for decision-making processes in higher education institutions

Vílchez‐Román

Sanguinetti²,

Mauricio-Salas

2020

LHT

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PurposeThe purpose of this paper is to analyse how using bibliometrics and information visualization can provide a “picture at glance” from which decision-makers can structure processes, thus organizing outputs/outcomes from inception.Design/methodology/approachThis study carried out a bibliometric-oriented review on studies on higher education students' retention; 1,962 records were downloaded from Scopus and grouped into three five-year intervals: 2002–2006 (n = 236), 2007–2011 (n = 584) and 2012–2016 (n = 1,142). Centrality measures and text-mining techniques were used to analyse data.FindingsClusters of academic networks were identified by using co-citation analysis. Also, terms with high semantic value were ranked and grouped by using automatic term extraction and co-word analysis.Practical implicationsThe bibliometric approach used in this study identifies clusters of authors specialized in student retention, as well as detects the primary terms within this research field.Originality/valueThis paper provides evidence that a bibliometric approach in conjunction with data visualization can be a valuable complement to in-depth literature reviews for the decision-making process.

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A visual approach to explainable computerized clinical decision support

Müller

Stöhr

Oeser

et al. 2020

Computers & Graphics

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Incorporating Uncertainty into Decision-Making: An Information Visualisation Approach

Cited by 4 publications

References 16 publications

Developing Visual-Assisted Decision Support Systems across Diverse Agricultural Use Cases

Developing Visual-Assisted Decision Support Systems across Diverse Agricultural Use Cases

Applied bibliometrics and information visualization for decision-making processes in higher education institutions

A visual approach to explainable computerized clinical decision support

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