Evidence map›Paper›PMID 40591578›Full record

ArticlePloS one2025

Bubble-Wall Plot as a Dynamic Analytical Processing Visualization Tool for Developing Visual Warning Systems: a Case Study.

Robert M X Wu, Huan Zhang, Jie Liang, Niusha Shafiabady, Hai Yan Helen Lu, Ergun Gide, D W M N C Dasanayake, Meena Jha, Shaoyang Duan

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In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Robert M X WuSchool of Professional Practice and Leadership, Faculty of Engineering and Information Technology, University of Technology Sydney, Australia.ORCID https://orcid.org/0000-0002-1735-6797
Huan ZhangSchool of Geography, Shanxi Normal University, Taiyuan, China.
Jie LiangVisualisation Institute, School of Computer Science, University of Technology Sydney, Australia.ORCID https://orcid.org/0000-0001-7179-5208
Niusha ShafiabadyDiscipline of IT, Australian Catholic University, North Sydney, Australia.
Hai Yan Helen LuSchool of Computer Science, Faculty of Engineering and Information Technology, University of Technology Sydney, Australia.
Ergun GideFaculty of Engineering and Technology, Central Queensland University, Sydney, Australia.
D W M N C DasanayakeSchool of Professional Practice and Leadership, Faculty of Engineering and Information Technology, University of Technology Sydney, Australia.ORCID https://orcid.org/0009-0009-9382-8707
Meena JhaFaculty of Engineering and Technology, Central Queensland University, Sydney, Australia.
Shaoyang DuanSchool of Professional Practice and Leadership, Faculty of Engineering and Information Technology, University of Technology Sydney, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper proposes a dynamic analytical processing (DAP) visualization tool based on the Bubble-Wall Plot. It can be handily used to develop visual warning systems for visualizing the dynamic analytical processes of hazard data. Comparative analysis and case study methods are used in this research. Based on a literature review of Q1 publications since 2017, 23 types of data visualization approaches/tools are identified, including seven anomaly data visualization tools. This study presents three significant findings by comparing existing data visualization approaches. The primary finding is that no single visualization tool can fully satisfy industry requirements. This finding motivates academics to develop new DAP visualization tools. The second finding is that there are different views of Line Charts and various perspectives on Scatter Plots. The other one is that different researchers may perceive an existing data visualization tool differently, such as arguments between Scatter Plots and Line Charts and diverse opinions about Parallel Coordinate Plots and Scatter Plots. Users' awareness rises when they choose data visualization tools that satisfy their requirements. By conducting a comparative analysis based on five categories (Style, Value, Change, Correlation, and Others) with 26 subcategories of metric features, results show that this new tool can effectively solve the limitations of existing visualization tools as it appears to have three remarkable characteristics: the simplest cartographic tool, the most straightforward visual result, and the most intuitive tool. Furthermore, this paper illustrates how the Bubble-Wall Plot can be effectively applied to develop a warning system for presenting dynamic analytical processes of hazard data in the coal mine. Lastly, this paper provides two recommendations, one implication, six research limitations, and eleven further study topics.

Indexed as

Data VisualizationComputer GraphicsHumansSoftware

Identifiers

PMID40591578
PMCPMC12212487

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.