Interactive Visualization Research Articles

The development of 'Petanque match statistics': an android-based application for petanque matches analysis

The accelerated pace of technological advancement necessitates that many disciplines align themselves with these developments, whether directly engaged in the process or not. The field of sports provides an illustrative example of the profound impact of modern technology on various disciplines. This research aimed to develop an Android-based statistical application, designated "Petanque Match Statistic," which was designed to analyze Petanque matches. The research and development (R&D) methodology was employed to undertake six project stages. The application, constructed on the Kodular platform, offers real-time data capture, sophisticated statistical analysis, interactive visualization, and comprehensive performance reporting. The application was subjected to rigorous alpha and beta testing to ensure its accuracy, reliability, and usability. Following its deployment, user training and a support system were established. Continuous evaluation and user feedback facilitated ongoing improvements. The application significantly enhances match analysis, benefiting players, coaches, analysts, and fans by providing accurate, real-time data and comprehensive insights, thereby promoting the growth and development of the sport of petanque. Keywords: Android Application, Match Statistics, Statistical Analysis, Real-Time Data, Sports Technology

Enhancing medical anatomy education with the integration of virtual reality into traditional lab settings.

In medical education, traditional anatomy labs have relied heavily on the hands-on dissection of cadavers to teach the complex spatial relationships within the human body. However, the advent of virtual reality (VR) technology offers the potential for significantly enhancing this traditional approach by providing immersive, interactive 3D visualizations that can overcome some of the limitations of physical specimens. This study explores the integration of VR into a traditional gross anatomy lab to enrich the learning experience for medical students. Methods included the deployment of a VR application developed to complement the dissection process, featuring detailed 3D models of human anatomy that students could manipulate and explore digitally. Approximately 60 s-year medical students participated in the lab, where they engaged with both traditional dissection and the VR application. Results indicated that the VR integration not only increased engagement and satisfaction but also improved the students' ability to understand anatomical structures and their spatial relationships. Moreover, feedback from students suggested more efficient learning and retention than with traditional methods alone. We conclude that VR technology can significantly enhance medical anatomy education by providing an adjunct to traditional dissection, potentially replacing certain aspects of physical specimens with digital simulations that offer repeatable, detailed exploration without the associated logistical and ethical constraints.

Scene understanding method utilizing global visual and spatial interaction features for safety production

Risk identification in power operations is crucial for both personal safety and power production. Existing risk identification methods mainly use target detection models to identify the common risks but the scene specificity of risk occurrence. For example, not wearing a safety harness, not wearing insulated gloves, etc. Since most methods for detecting safety gears make sense only under specific scene. But the power electric work is a complex object involving many elements such as personnel, equipment and safety tools. Therefore, this paper proposes a scene understanding method that integrates visual features and spatial relationship features among scene elements. This method constructs a scenean undirected scene graph to represent the interactive relationship among the elements, extracts the interactive features by using a graph encoder-decoder convolution module, and fuse perceived high-dimensional visual features and spatial topological features for scene recognition, in order to effectively solve addressing the power operation scene understanding problem under multi-element interaction. Finally, a power inspection operation scenario was chosen as the test case. The outcome of the evaluation indicates results indicate that the proposed approach suggested in this study exhibits superior precision in scene identification and shows ademonstrates strong generalization ability.

Mesoscale Explorer - Visual Exploration of Large-Scale Molecular Models.

The advent of cryo-electron microscopy (cryo-EM) and cryo-electron tomography (cryo-ET), coupled with computational modeling, has enabled the creation of integrative 3D models of viruses, bacteria, and cellular organelles. These models, composed of thousands of macromolecules and billions of atoms, have historically posed significant challenges for manipulation and visualization without specialized molecular graphics tools and hardware. With the recent advancements in GPU rendering power and web browser capabilities, it is now feasible to render interactively large molecular scenes directly on the web. In this work, we introduce Mesoscale Explorer, a web application built using the Mol* framework, dedicated to the visualization of large-scale molecular models ranging from viruses to cell organelles. Mesoscale Explorer provides unprecedented access and insight into the molecular fabric of life, enhancing perception, streamlining exploration, and simplifying visualization of diverse data types, showcasing the intricate details of these models with unparalleled clarity.

Interactive 2D Visualizations of Olomouc's Development as Tools for Revitalizing Cultural Heritage

Interactive 2D Visualizations of Olomouc's Development as Tools for Revitalizing Cultural Heritage

Housing customization: envisioning an interface to support co-design processes

PurposeThere are several studies showing that end-users' participation in the architectural design process of houses is critical to their satisfaction (e.g. Önder et al., 2010; Ammar et al., 2013). Housing that is not adjusted to inhabitants' needs leads to modification works (Davidson et al., 2007) that could be avoided if their design was defined from the beginning with their participation. Digital technologies, such as 3D interactive visualization, benefit co-design processes by helping non-specialists better understand space and design possibilities (Salter et al., 2009; Schroth et al., 2006). However, the available literature shows that existing co-design digital tools were not developed based on potential users’ requirements. This paper aims to define the user requirements of a co-design tool for housing customization.Design/methodology/approachInterviews were conducted to gather information on how participatory processes occur in housing cooperatives and identify how potential users can collaborate in the design definition of their houses using a digital tool.FindingsThe interviews were analyzed, and requirements were defined.Originality/valueThis work contributes to the advancement of knowledge since the tool is defined based on requirements collected from potential end-users. By using a user-centered approach, the tool can contribute to more effective and informed collaboration.

Interactive visualizations for assessing car-to-bicycle overtaking manoeuvres

Interactive visualizations for assessing car-to-bicycle overtaking manoeuvres

A Digital Twin of the Trondheim Fjord for Environmental Monitoring—A Pilot Case

Digital Twins of the Ocean (DTO) are a rapidly emerging topic that has attracted significant interest from scientists in recent years. The initiative, strongly driven by the EU, aims to create a digital replica of the ocean to better understand and manage marine environments. The Iliad project, funded under the EU Green Deal call, is developing a framework to support multiple interoperable DTO using a federated systems-of-systems approach across various fields of applications and ocean areas, called pilots. This paper presents the results of a Water Quality DTO pilot located in the Trondheim fjord in Norway. This paper details the building blocks of DTO, specific to this environmental monitoring pilot. A crucial aspect of any DTO is data, which can be sourced internally, externally, or through a hybrid approach utilizing both. To realistically twin ocean processes, the Water Quality pilot acquires data from both surface and benthic observatories, as well as from mobile sensor platforms for on-demand data collection. Data ingested into an InfluxDB are made available to users via an API or an interface for interacting with the DTO and setting up alerts or events to support ’what-if’ scenarios. Grafana, an interactive visualization application, is used to visualize and interact with not only time-series data but also more complex data such as video streams, maps, and embedded applications. An additional visualization approach leverages game technology based on Unity and Cesium, utilizing their advanced rendering capabilities and physical computations to integrate and dynamically render real-time data from the pilot and diverse sources. This paper includes two case studies that illustrate the use of particle sensors to detect microplastics and monitor algae blooms in the fjord. Numerical models for particle fate and transport, OpenDrift and DREAM, are used to forecast the evolution of these events, simulating the distribution of observed plankton and microplastics during the forecasting period.

Strategi Komunikasi Pendidikan untuk Meningkatkan Kualitas Pendidikan di Era Gen Z

This study discusses educational communication strategies to improve the quality of education in the Generation Z era, which requires a communication approach that suits the unique characteristics influenced by technology. Using a qualitative approach and literature analysis, the research aims to identify effective educational communication strategies for Generation Z. Key findings include visual preferences, personalization, interactivity, problem-based learning, immersive technology, digital mentoring, flexibility, and social responsibility. Recommended strategies include visual content, adaptive learning, online discussions, VR/AR, digital mentoring, mobile learning, social projects, gamification, and multi-platform communication. It is important to understand the characteristics of Generation Z and adapt in relevant and effective ways, as well as create education that is technologically advanced and of great value. Implementation suggestions include digital teacher training, online cultural diplomacy, and educational media policies. This research provides valuable guidance for the development of educational strategies that suit the needs of Z Generation.

Rvisdiff: An R package for interactive visualization of differential expression.

Rvisdiff is an R/Bioconductor package that generates an interactive interface for the interpretation of differential expression results. It creates a local web page that enables the exploration of statistical analysis results through the generation of auto-analytical visualizations. Users can explore the differential expression results and the source expression data interactively in the same view. As input, the package supports the results of popular differential expression packages such as DESeq2, edgeR, and limma. As output, the package generates a local HTML page that can be easily viewed in a web browser. Rvisdiff is freely available at https://bioconductor.org/packages/Rvisdiff/.

Design Concerns for Integrated Scripting and Interactive Visualization in Notebook Environments.

Interactive visualization can support fluid exploration but is often limited to predetermined tasks. Scripting can support a vast range of queries but may be more cumbersome for free-form exploration. Embedding interactive visualization in scripting environments, such as computational notebooks, provides an opportunity to leverage the strengths of both direct manipulation and scripting. We investigate interactive visualization design methodology, choices, and strategies under this paradigm through a design study of calling context trees used in performance analysis, a field which exemplifies typical exploratory data analysis workflows with Big Data and hard to define problems. We first produce a formal task analysis assigning tasks to graphical or scripting contexts based on their specificity, frequency, and suitability. We then design a notebook-embedded interactive visualization and validate it with intended users. In a follow-up study, we present participants with multiple graphical and scripting interaction modes to elicit feedback about notebook-embedded visualization design, finding consensus in support of the interaction model. We report and reflect on observations regarding the process and design implications for combining visualization and scripting in notebooks.

Explainable Artificial Intelligence for Early Prediction of Pressure Injury Risk.

Hospital-acquired pressure injuries (HAPIs) have a major impact on patient outcomes in intensive care units (ICUs). Effective prevention relies on early and accurate risk assessment. Traditional risk-assessment tools, such as the Braden Scale, often fail to capture ICU-specific factors, limiting their predictive accuracy. Although artificial intelligence models offer improved accuracy, their "black box" nature poses a barrier to clinical adoption. To develop an artificial intelligence-based HAPI risk-assessment model enhanced with an explainable artificial intelligence dashboard to improve interpretability at both the global and individual patient levels. An explainable artificial intelligence approach was used to analyze ICU patient data from the Medical Information Mart for Intensive Care. Predictor variables were restricted to the first 48 hours after ICU admission. Various machine-learning algorithms were evaluated, culminating in an ensemble "super learner" model. The model's performance was quantified using the area under the receiver operating characteristic curve through 5-fold cross-validation. An explainer dashboard was developed (using synthetic data for patient privacy), featuring interactive visualizations for in-depth model interpretation at the global and local levels. The final sample comprised 28 395 patients with a 4.9% incidence of HAPIs. The ensemble super learner model performed well (area under curve = 0.80). The explainer dashboard provided global and patient-level interactive visualizations of model predictions, showing each variable's influence on the risk-assessment outcome. The model and its dashboard provide clinicians with a transparent, interpretable artificial intelligence-based risk-assessment system for HAPIs that may enable more effective and timely preventive interventions.

KnowledgeVIS: Interpreting Language Models by Comparing Fill-in-the-Blank Prompts.

Recent growth in the popularity of large language models has led to their increased usage for summarizing, predicting, and generating text, making it vital to help researchers and engineers understand how and why they work. We present KnowledgeVIS, a human-in-the-loop visual analytics system for interpreting language models using fill-in-the-blank sentences as prompts. By comparing predictions between sentences, KnowledgeVIS reveals learned associations that intuitively connect what language models learn during training to natural language tasks downstream, helping users create and test multiple prompt variations, analyze predicted words using a novel semantic clustering technique, and discover insights using interactive visualizations. Collectively, these visualizations help users identify the likelihood and uniqueness of individual predictions, compare sets of predictions between prompts, and summarize patterns and relationships between predictions across all prompts. We demonstrate the capabilities of KnowledgeVIS with feedback from six NLP experts as well as three different use cases: (1) probing biomedical knowledge in two domain-adapted models; and (2) evaluating harmful identity stereotypes and (3) discovering facts and relationships between three general-purpose models.

Studying Retroviral Life Cycles Using Visible Viruses and Live Cell Imaging.

Viruses exploit key host cell factors to accomplish each individual stage of the viral replication cycle. To understand viral pathogenesis and speed the development of new antiviral strategies, high-resolution visualization of virus-host interactions is needed to define where and when these events occur within cells. Here, we review state-of-the-art live cell imaging techniques for tracking individual stages of viral life cycles, focusing predominantly on retroviruses and especially human immunodeficiency virus type1, which is most extensively studied. We describe how visible viruses can be engineered for live cell imaging and how nonmodified viruses can, in some instances, be tracked and studied indirectly using cell biosensor systems. We summarize the ways in which live cell imaging has been used to dissect the retroviral life cycle. Finally, we discuss select challenges for the future including the need for better labeling strategies, increased resolution, and multivariate systems that will allow for the study of full viral replication cycles.

On-demand mitral valve morphometrics during surgical repair

Abstract Mitral valve regurgitation is one of the most common heart valve diseases that can occur when the structural composition of the mitral valve is affected. Mitral valve repair, typically performed in a minimally invasive setting, is a complex surgery that aims to reinstate the structural integrity of the valve and thereby restore normal valve function. The current practice lacks quantification of geometrical changes and interactive 3D visualization that could enhance the understanding of pathomorphological changes and impact of surgical correction. This work presents functionalities from smartMVR, a quantitative tool to measure, compare, and analyse changes in mitral valve geometry from data captured on-demand using an RGB-D camera. The feasibility of the approach is demonstrated on a silicone replica of a pathological mitral valve that is iteratively corrected using common surgical techniques.

Sonic Electromagnetism

The author describes their sound art practice, which uses the electromagnetic field (EM) to explore concepts of the body toward a feminist and pro-trans future. This practice stands in contrast to hidden consumer “black box” culture and mediated digital telepresence. Three specific art projects are explored that fuse visual design, printed circuitry, and interactivity to build critical space for participatory exploration. The author explores concepts of the body in relation to spatialized sound and queer phenomenology of sound. Lastly, the author suggests that the creative exploration of sonic electromagnetism is a larger movement by a disparate community of artists who aim to challenge existing systems of power. In their exploration of the electromagnetic field, the author argues that these artists strive to harness a new source of empowerment and spirit.

A Proposed Framework for integrating IVR Technology in Architectural Design courses; Application on architectural schools in Egypt

Abstract Visual communication has a vital role in the architecture. Virtual reality (VR) is one of the various methods of visual communication and interaction, especially during pandemics. Although it has many benefits such as improved space perception and dimension visualization etc., it’s not commonly used in Egyptian architectural schools. This research aims to investigate the integration of Immersive Virtual Reality (IVR) into the design curriculums in Egyptian architectural schools and to propose a framework for its integration. A mixed method approach was used in this study along with the literature data that was reviewed to identify the benefits, limitations and different IVR setups. First, an interview was conducted with one of the VRCAVE founders in an Egyptian private university to understand the effect of IVR and whether it has affected the students’ outcome. This was followed by conducting an experiment including an IVR setup along with a 3D Virtual model, to conduct semi-structured interview with the participants to analyse the use of IVR in the design modules and whether its integration in the architecture schools design curriculum would be beneficial

AnnoMate: Exploring and annotating integrated molecular data through custom interactive visualizations

AnnoMate: Exploring and annotating integrated molecular data through custom interactive visualizations

Impact of interaction technique in interactive data visualisations: A study on lookup, comparison, and relation-seeking tasks

This paper presents an analysis of different interaction techniques used in interactive data visualisations to support end-users in visual analytics tasks. Our selection of interaction techniques is based on prior work and consists of the interaction techniques Select, Explore, Reconfigure, Encode, Filter, Abstract/Elaborate, and Connect. Through a within-subject study, we assessed participants’ abilities to utilise these techniques when faced with three distinct types of data-driven tasks; lookup, comparison, and Relation-seeking. Our research investigates the impact of these interaction techniques on the correctness, confidence, perceived difficulty, and cognitive load of N = 80 self-identified data scientists and N = 80 non-experts. We find that interaction technique significantly impacts answer correctness and participant confidence. Participants performed best across those interaction techniques that allow for information that is deemed least relevant to be concealed, which is reflected in lower intrinsic and extraneous cognitive load. Interestingly, participants’ expertise affected their confidence but not their accuracy. Our results provide insights useful for a more targeted and informed design and usage of interactive data visualisations.

XR-based interactive visualization platform for real-time exploring dynamic earth science data

The transition from 2D planar displays to immersive holographic 3D environments has brought advancements in visualization technology. However, there remains a lack of effective interactive visualization tools for complex multi-dimensional structured or unstructured datasets in immersive space. To address this gap, we have developed MetIVA, a state-of-the-art multiscale interactive data visualization platform that leverages the Extended Reality (XR) and cloud rendering technology for immersive data exploration. In this paper, we firstly outline the historical development of scientific visualization and the recent shift towards 3D and higher-dimensional visualization, and then basically introduce the conceptual framework and platform structure of MetIVA, and finally present the evaluation results from recruited potential users. The results confirm that MetIVA is a powerful tool to accelerate data exploration and decision-making processes. Its interactive and intuitive features, along with ongoing optimization efforts, make it a valuable tool for researchers and practitioners in the field of Earth science.