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Data Visualization Techniques: Advances and Applications
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Data Visualization Techniques: Advances and Applications

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 4397

Special Issue Editors

Dr. Javier Sevilla

E-Mail Website
Guest Editor
Institute of Robotics and Information and Communication Technologies (IRTIC), Universitat de València, 46980 Paterna, Spain
Interests: virtual reality interaction
Prof. Dr. Kwan-Hee Yoo

E-Mail Website
Guest Editor
Department of Computer Science, Chungbuk National University, Cheongju 28644, Republic of Korea
Interests: big data analysis; data visualization; visual analytics; smart manufacturing; virtual reality; augmented reality
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The advent of big data has highlighted the usefulness and importance of transforming large datasets into information, which is often essential for decision making in various scientific and technological areas. Data visualization techniques have also evolved, allowing researchers and practitioners to explore and exploit complex information effectively. From interactive graphics to immersive visualizations in augmented and virtual reality, these techniques have created new possibilities for data interpretation.

This Special Issue discusses the recent advances in data visualization techniques and their practical applications in detail. It will show how innovative tools facilitate the understanding of complex data in fields as diverse as cultural heritage analysis, artificial intelligence, medicine, and others. A series of case studies and articles will demonstrate how data visualization techniques improve scientific communication and drive new discoveries in various scientific fields. These works will be essential for understanding the state of data visualization, where the convergence of science and technology has revealed patterns that would otherwise remain hidden.

Dr. Javier Sevilla
Prof. Dr. Kwan-Hee Yoo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • visualization literacy
  • data visualization
  • computer graphics
  • visual analytics
  • virtual reality
  • immersive visualization

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Published Papers (4 papers)

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Research

16 pages, 846 KiB  
Article
Development of an Anomaly Classification Model and a Decision Support Tool for Firewall Policy Configuration
by Jinyong Park, Byeongjo Park and Tae-Sung Kim
Appl. Sci. 2025, 15(6), 2979; https://doi.org/10.3390/app15062979 - 10 Mar 2025
Viewed by 512
Abstract
A firewall is a device that is used generally to prevent cyberattacks and protect internal assets by blocking unauthorized access. Information security managers have many difficulties in managing firewall policies due to errors or anomalies in the policy that are caused by frequent [...] Read more.
A firewall is a device that is used generally to prevent cyberattacks and protect internal assets by blocking unauthorized access. Information security managers have many difficulties in managing firewall policies due to errors or anomalies in the policy that are caused by frequent internal and external requests. This paper intends to develop an anomaly classification model to detect anomalies and measure the priority of resolution in firewall policy as well as a visualized tool that supports information security managers to manage their firewall policy efficiently. This model and tool help information security managers resolve anomalies in firewall policy, enable efficient firewall policy management, and protect internal assets effectively. Full article
(This article belongs to the Special Issue Data Visualization Techniques: Advances and Applications)
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17 pages, 17183 KiB  
Article
The Implementation of a WebGPU-Based Volume Rendering Framework for Interactive Visualization of Ocean Scalar Data
by Jiaqi Yu, Rufu Qin and Zhounan Xu
Appl. Sci. 2025, 15(5), 2782; https://doi.org/10.3390/app15052782 - 5 Mar 2025
Viewed by 721
Abstract
Visualization contributes to an in-depth understanding of ocean variables and phenomena, and a web-based three-dimensional visualization of ocean data has gained significant attention in oceanographic research. However, many challenges remain to be addressed while performing a real-time interactive visualization of large-volume heterogeneous scalar [...] Read more.
Visualization contributes to an in-depth understanding of ocean variables and phenomena, and a web-based three-dimensional visualization of ocean data has gained significant attention in oceanographic research. However, many challenges remain to be addressed while performing a real-time interactive visualization of large-volume heterogeneous scalar datasets in a web environment. In this study, we propose a WebGPU-based volume rendering framework for an interactive visualization of ocean scalar data. The ray casting algorithm, optimized with early ray termination and adaptive sampling methods, is adopted as the core volume rendering algorithm to visualize three-dimensional gridded data preprocessed from regular and irregular gridded volume datasets generated by ocean numerical modeling, utilizing the Babylon.js rendering engine and WebGPU technology. Moreover, the framework integrates a set of interactive visual analysis tools, providing functionalities such as volume cutting, value-based spatial data filtering, and time-series animation playback, enabling users to effectively display, navigate, and explore multidimensional datasets. Finally, we conducted several experiments to evaluate the visual effects and performance of the framework. The results suggest that the proposed WebGPU-based volume rendering framework is a feasible web-based solution for visualizing and analyzing large-scale gridded ocean scalar data. Full article
(This article belongs to the Special Issue Data Visualization Techniques: Advances and Applications)
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20 pages, 14223 KiB  
Article
NDEExplorer: Visual Analytics for Exploring Damage Modes via Multimodal Data in the Non-Destructive Examination of Composite Materials
by Dongliang Guo, Lisha Zhou and Xingfa Luo
Appl. Sci. 2025, 15(2), 952; https://doi.org/10.3390/app15020952 - 19 Jan 2025
Viewed by 733
Abstract
Non-destructive examination (NDE) in the field of materials engineering is a technique based on acoustics and optical principles used for detecting and evaluating internal defects in materials without causing any damage. The majority of current research on material damage focuses on the analysis [...] Read more.
Non-destructive examination (NDE) in the field of materials engineering is a technique based on acoustics and optical principles used for detecting and evaluating internal defects in materials without causing any damage. The majority of current research on material damage focuses on the analysis of a single NDE method, resulting in low correlation between different NDE methods, and their results are frequently presented as complex data and images, making it difficult for professionals to obtain intuitive inspection results. Therefore, we propose a visual analytics system, NDEExplorer, aimed at solving these problems through visual analytics techniques. The system supports the use of two NDE methods, Acoustic Emission (AE) and Digital Image Correlation (DIC), providing interactive and intuitive views for observing composite material damage features. In addition, the system features a fusion analysis approach and a view that combines AE and DIC methods, enabling users to explore the correlations and trends in multimodal data generated during the material damage process. For users, the application of this system can help accurately identify the various material damage stages and their accompanying damage modes. To evaluate the effectiveness of the proposed method, we conduct a case study using two modal datasets from the same composite material damage scenario and carry out qualitative interviews with professionals and graduate students in the field. Finally, the quantitative feedback from a user study confirms the usefulness of our visual system for the multimodal analysis of material damage datasets. Full article
(This article belongs to the Special Issue Data Visualization Techniques: Advances and Applications)
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27 pages, 3277 KiB  
Article
ShinyAnonymizer Enhanced Version and Beyond: A Further Exploration of Privacy-Preserving Solutions in Health Data Management
by Marios Vardalachakis, Nikos Papadakis and Manolis Tampouratzis
Appl. Sci. 2024, 14(16), 6921; https://doi.org/10.3390/app14166921 - 7 Aug 2024
Cited by 1 | Viewed by 1650
Abstract
Healthcare institutions generate massive amounts of valuable patient data in the digital age. Finding the right balance between patient privacy and the demand for data-driven medical enhancements is essential. Since data privacy has become increasingly important, robust technologies must be developed to safeguard [...] Read more.
Healthcare institutions generate massive amounts of valuable patient data in the digital age. Finding the right balance between patient privacy and the demand for data-driven medical enhancements is essential. Since data privacy has become increasingly important, robust technologies must be developed to safeguard private data and allow meaningful exploration. This issue was addressed by ShinyAnonymizer, which was first created to anonymize health data. It achieves this by rendering anonymization methods easily available to users. The enhanced version of ShinyAnonymizer, with an essential improvement in performance, is presented in this study. We explain the merging of data analysis, visualization, and privacy-focused statistics paradigms with data anonymization, hashing, and encryption, offering researchers and data analysts an extensive collection of tools for trustworthy data management. Full article
(This article belongs to the Special Issue Data Visualization Techniques: Advances and Applications)
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