Web-based Data Visualization Research Articles

PlayMolecule Viewer: A Toolkit for the Visualization of Molecules and Other Data.

PlayMolecule Viewer is a web-based data visualization toolkit designed to streamline the exploration of data resulting from structural bioinformatics or computer-aided drug design efforts. By harnessing state-of-the-art web technologies such as WebAssembly, PlayMolecule Viewer integrates powerful Python libraries directly within the browser environment, which enhances its capabilities to manage multiple types of molecular data. With its intuitive interface, it allows users to easily upload, visualize, select, and manipulate molecular structures and associated data. The toolkit supports a wide range of common structural file formats and offers a variety of molecular representations to cater to different visualization needs. PlayMolecule Viewer is freely accessible at open.playmolecule.org, ensuring accessibility and availability to the scientific community and beyond.

The Development of a Clinical Registry Digital Database on Invasive Fungal Infections in India: Advancing Epidemiological Understanding and Patient Care.

A well-structured digital database is essential for any national priority project as it can provide real-time data analysis and facilitate quick decision making. In recent times, particularly after the COVID-19 pandemic, invasive fungal infections (IFIs) have emerged as a significant public health challenge in India, affecting vulnerable population, including immunocompromised individuals. The lack of comprehensive and well-structured data on IFIs has hindered efforts to understand their true burden and optimize patient care. To address this critical knowledge gap, the ICMR has undertaken a Pan-India pioneer initiative to develop a network of Advanced Mycology Diagnostic research centres in different geographical zones of the country (ICMR-MycoNet). Under the aegis of this project, a clinical registry on IFIs in the ICUs is initiated. This process paper presents a detailed account of the steps involved in the establishment of a web-based data entering and monitoring platform to capture data electronically, ensuring robust and secure data collection and management. This system not only allows participating ICMR-MycoNet centres to enter patient information directly into the database using standardized Case Report Form (CRF) but also includes data validation checks to ensure the accuracy and completeness of entered data. It is complemented by a real-time, web-based, and adaptable data visualization platform. This registry aims to provide crucial epidemiological insights, promote evidence-based hospital infection control programs, and ultimately improve patient outcomes in the face of this formidable healthcare challenge.

Data Visualization Analysis in the Management Information System for Submitting Credit Scores for Education Personnel

Education staff have an important role in facilitating the implementation of the tridharma of higher education and are an indicator of educational administration success. This study looks at how data visualization was implemented in the Management Information System for Submitting Credit Scores for Education Personnel. The research is primarily concerned with the Functional Position of Intermediate Expert Computer Staff. The study's goal is to create web-based data visualization tools to enable submitting and assessing credit scores for Intermediate Computer Experts easier, thereby meeting the requirement for efficiency and accuracy in the promotion and position process. This study employs a research and development (R&D) methodology with an iterative prototype approach. The initial step involves a needs analysis, including an in-depth understanding of the Associate Computer Expert promotion process and the associated administrative requirements. Next, a web-based data visualization prototype was designed, which included an intuitive user interface, database integration, and a credit number calculation algorithm. The prototype was then implemented and tested on a limited basis in the IPDN environment. The proposed system is designed to provide easy access, facilitate data verification, and enable computerized sorting and calculation of credit numbers. The main contribution of this research lies in developing information technology solutions that can increase the transparency and effectiveness of administrative processes in the IPDN environment. It is hoped that the output of this research can provide conceptual and practical contributions to managing the credit figures for educational staff and provide a basis for developing similar systems in other educational institutions.

GERDH: an interactive multi-omics database for cross-species data mining in horticultural crops.

Horticultural plants contribute immensely to the quality of humans' life. The rapid development of omics studies on horticultural plants has resulted in large volumes of valuable growth- and development-related data. Genes that are essential for growth and development are highly conserved in evolution. Cross-species data mining reduces the impact of species heterogeneity and has been extensively used for conserved gene identification. Owing to the lack of a comprehensive database for cross-species data mining using multi-omics data from all horticultural plant species, the current resources in this field are far from satisfactory. Here, we introduce GERDH (https://dphdatabase.com), a database platform for cross-species data mining among horticultural plants, based on 12,961 uniformly processed publicly available omics libraries from more than 150 horticultural plant accessions, including fruits, vegetables, and ornamental plants. Important and conserved genes that are essential for a specific biological process can be obtained by cross-species analysis module with interactive web-based data analysis and visualization. Moreover, GERDH is equipped with 7 online analysis tools, including gene expression, in-species analysis, epigenetic regulation, gene co-expression, enrichment/pathway and phylogenetic analysis. By interactive cross-species analysis, we identified key genes contributing to postharvest storage. By gene expression analysis, we explored new functions of CmEIN3 in flower development, which was validated by transgenic chrysanthemum analysis. We believe that GERDH will be a useful resource for key gene identification and will allow for omics big data to be more available and accessible to horticultural plant community members.

A Platform for Data-Centric, Continuous Epidemiological Analyses (EpiGraphHub): Descriptive Analysis.

Guaranteeing durability, provenance, accessibility, and trust in open data sets can be challenging for researchers and organizations that rely on public repositories of data critical for epidemiology and other health analytics. The required data repositories are often difficult to locate and may require conversion to a standard data format. Data-hosting websites may also change or become unavailable without warning. A single change to the rules in one repository can hinder updating a public dashboard reliant on data pulled from external sources. These concerns are particularly challenging at the international level, because policies on systems aimed at harmonizing health and related data are typically dictated by national governments to serve their individual needs. In this paper, we introduce a comprehensive public health data platform, EpiGraphHub, that aims to provide a single interoperable repository for open health and related data. The platform, curated by the international research community, allows secure local integration of sensitive data while facilitating the development of data-driven applications and reports for decision-makers. Its main components include centrally managed databases with fine-grained access control to data, fully automated and documented data collection and transformation, and a powerful web-based data exploration and visualization tool. EpiGraphHub is already being used for hosting a growing collection of open data sets and for automating epidemiological analyses based on them. The project has also released an open-source software library with the analytical methods used in the platform. The platform is fully open source and open to external users. It is in active development with the goal of maximizing its value for large-scale public health studies.

How’s Our Library E-Service? Measuring User Satisfaction in the Virtual Environment

Objective. This study aims to determine the satisfaction with the virtual reference service of library users of Nazarbayev University Library during the Spring 2021 to Spring 2022 semesters. Methods. This study employed a descriptive approached to determine the satisfaction of users with the virtual service of Nazarbayev University Library during the Spring 2021 to Spring 2022 semesters. Using the data gathered from LibAnswers’ Quality of Service (QoS), this study examines various metrics in answering the queries received both in synchronous (chat service) or asynchronous (email service) virtual service. Statistical data from were tabulated and analyzed and the feedback from patrons will be interpreted using Voyant Tools, a web-based data visualization software. Results. The study describe how patrons were satisfied with the virtual library service of NU Library as perceived through their feedback and their overall experience of the service. In addition, the study pointed out that the Library considers all virtual transactions urgent and put the satisfaction of their patrons on top priority based on the metrics. Conclusions. The study revealed that patrons were satisfied with the virtual service rendered by NU Library both in synchronous and asynchronous format. With the help of the metrics generated from LibAnswers Quality of Service (QoS) feature, the NU Library was able to provide an excellent service despite the limitations brought by the pandemic. The feedback from patrons was indeed a proof of their satisfaction. As service quality and user satisfaction will always go together, the library, as a service-oriented information arm of any institution, should always put their patrons as their top priority.

A new remote web-based MDSplus data visualization system for EAST

WebScope has been widely used in the Experimental Advanced Superconducting Tokamak (EAST) experiment for many years. The choice of the Java applet technology for its implementation has been successful, which allows for pulse data communication and instant feedback through various web browsers. Accessing MDSplus data with it however brings some inconvenience due to the majority of browsers have dropped support for Java plugin. Recently, a new web-based MDSplus data visualization system with the MVVM (Model–View–ViewModel) architecture has been developed. The flexibility brought by using JavaScript middle components in the architecture reduces the program coupling and improves the system availability. A further availability is proposed here, that is, using reverse proxy mechanism to publish the abstract interfaces provided by MDSplus separately from the visual resources, with the proxy to specify data request relationships. For incoming network traffic in the server pool, effective load balancing is ensured. The slice storage mechanism in MDSplus and thumbnail are now used for storing and reading long pulse data, and exporting data through proxy ports which ensures secure access to experimental data. Pulse access variables are also stored in cloud server for authorized users to share across devices. The system was successfully applied to EAST experiment and achieved good performance. The design details of the system are described in this paper.

Cancer Data Visualization: Developing Tools to Serve the Needs of Diverse Stakeholders

AbstractPurpose of reviewTo describe how cancer data visualization tools can catalyze novel research and inform local cancer control planning.Recent findingsIn recent years, cancer centers across the nation have increasingly embraced geospatial tools to respond to the unique distributions of disease and multilevel risk factors within their catchment areas. Sylvester Comprehensive Cancer Center in Miami, Florida, recently developed a publicly available, interactive, web-based cancer data visualization tool called SCAN360. Using SCAN360 as an example, we discuss key considerations and challenges for the development of cancer data visualization tools that serve the needs of stakeholders in community, academic and government settings.SummaryCancer data visualization tools are useful for stakeholders from diverse sectors and may facilitate a range of cancer control efforts, from identifying regions for targeted outreach and engagement, to informing the allocation of resources for government and community initiatives, and motivating collaborative, interdisciplinary cancer research.

Introducing the combined atlas framework for large-scale web-based data visualization: The GloNAF atlas of plant invasion.

Large‐scale biodiversity data, for example, on species distribution and richness information, are being mobilized and becoming available at an increasing rate. Interactive web applications like atlases have been developed to visualize available datasets and make them accessible to a wider audience. Web mapping tools are changing rapidly, and different underlying concepts have been developed to visualize datasets at a high cartographic standard.Here, we introduce the Combined Atlas Framework for the development of interactive web atlases for ecological data visualization. We combine two existing approaches: the five stages of the user‐centred design approach for web mapping applications and the three U approach for interface success.Subsequently, we illustrate the use of this framework by developing the Atlas of Plant Invasions based on the Global Naturalized Alien Flora (GloNAF) database. This case study illustrates how the newly developed Combined Atlas Framework with a user‐centred design philosophy can generate measurable success through communication with the target user group, iterative prototyping and competitive analysis of other existing web mapping approaches.The framework is useful in creating an atlas that employs user feedback to determine usability and utility features within an interactive atlas system. Finally, this framework will enable a better‐informed development process of future visualization and dissemination of biodiversity data through web mapping applications and interactive atlases.

Near real-time streaming analysis of big fusion data

Experiments on fusion plasmas produce high-dimensional data time series with ever-increasing magnitude and velocity, but turn-around times for analysis of this data have not kept up. For example, many data analysis tasks are often performed in a manual, ad-hoc manner some time after an experiment. In this article, we introduce the Delta framework that facilitates near real-time streaming analysis of big and fast fusion data. By streaming measurement data from fusion experiments to a high-performance compute center, Delta allows computationally expensive data analysis tasks to be performed in between plasma pulses. This article describes the modular and expandable software architecture of Delta and presents performance benchmarks of individual components as well as of an example workflow. Focusing on a streaming analysis workflow where electron cyclotron emission imaging (ECEi) data is measured at KSTAR on the National Energy Research Scientific Computing Center’s (NERSC’s) supercomputer we routinely observe data transfer rates of about 4 Gigabit per second. In NERSC, a demanding turbulence analysis workflow effectively utilizes multiple nodes and graphical processing units and executes them in under 5 min. We further discuss how Delta uses modern database systems and container orchestration services to provide web-based real-time data visualization. For the case of ECEi data we demonstrate how data visualizations can be augmented with outputs from machine learning models. By providing session leaders and physics operators, results of higher-order data analysis using live visualizations may make more informed decisions on how to configure the machine for the next shot.

Quantitative visualization of physical barriers for vulnerable pedestrians based on photogrammetry

PurposeThe purpose of this study is to propose a method for vulnerable pedestrians to visualize potential obstacles on sidewalks. In recent years, the number of vulnerable pedestrians has been increasing as Japanese society has aged. The number of wheelchair users is also expected to increase in the future. Currently, barrier-free maps and street-view applications can be used by wheelchair users to check possible routes and the surroundings of their destinations in advance. However, identifying physical barriers that pose a threat to vulnerable pedestrians en route is often difficult.Design/methodology/approachThis study uses photogrammetry to create a digital twin of the three-dimensional (3D) geometry of the existing walking space by collecting photographic images taken on sidewalks. This approach allows for the creation of high-resolution digital elevation models of the entire physical sidewalk surface from which physical barriers such as local gradients and height differences can be detected by uniform image filtering. The method can be used with a Web-based data visualization tool in a geographical information system, permitting first-person views of the ground and accurate geolocation of the barriers on the map.FindingsThe findings of this study showed that capturing the road surface with a small wide-angle camera while walking is sufficient for recording subtle 3D undulations in the road surface. The method used for capturing data and the precision of the 3D restoration results are described.Originality/valueThe proposed approach demonstrates the significant benefits of creating a digital twin of walking space using photogrammetry as a cost-effective means of balancing the acquisition of 3D data that is sufficiently accurate to show the detailed geometric features needed to navigate a walking space safely. Further, the findings showed how information can be provided directly to users through two-dimensional (2D) and 3D Web-based visualizations.

Gosling: A Grammar-based Toolkit for Scalable and Interactive Genomics Data Visualization.

The combination of diverse data types and analysis tasks in genomics has resulted in the development of a wide range of visualization techniques and tools. However, most existing tools are tailored to a specific problem or data type and offer limited customization, making it challenging to optimize visualizations for new analysis tasks or datasets. To address this challenge, we designed Gosling-a grammar for interactive and scalable genomics data visualization. Gosling balances expressiveness for comprehensive multi-scale genomics data visualizations with accessibility for domain scientists. Our accompanying JavaScript toolkit called Gosling.js provides scalable and interactive rendering. Gosling.js is built on top of an existing platform for web-based genomics data visualization to further simplify the visualization of common genomics data formats. We demonstrate the expressiveness of the grammar through a variety of real-world examples. Furthermore, we show how Gosling supports the design of novel genomics visualizations. An online editor and examples of Gosling.js, its source code, and documentation are available at https://gosling.js.org.

Imaging-Based Machine Learning Analysis of Patient-Derived Tumor Organoid Drug Response

Three-quarters of compounds that enter clinical trials fail to make it to market due to safety or efficacy concerns. This statistic strongly suggests a need for better screening methods that result in improved translatability of compounds during the preclinical testing period. Patient-derived organoids have been touted as a promising 3D preclinical model system to impact the drug discovery pipeline, particularly in oncology. However, assessing drug efficacy in such models poses its own set of challenges, and traditional cell viability readouts fail to leverage some of the advantages that the organoid systems provide. Consequently, phenotypically evaluating complex 3D cell culture models remains difficult due to intra- and inter-patient organoid size differences, cellular heterogeneities, and temporal response dynamics. Here, we present an image-based high-content assay that provides object level information on 3D patient-derived tumor organoids without the need for vital dyes. Leveraging computer vision, we segment and define organoids as independent regions of interest and obtain morphometric and textural information per organoid. By acquiring brightfield images at different timepoints in a robust, non-destructive manner, we can track the dynamic response of individual organoids to various drugs. Furthermore, to simplify the analysis of the resulting large, complex data files, we developed a web-based data visualization tool, the Organoizer, that is available for public use. Our work demonstrates the feasibility and utility of using imaging, computer vision and machine learning to determine the vital status of individual patient-derived organoids without relying upon vital dyes, thus taking advantage of the characteristics offered by this preclinical model system.

A Web-Based Rendering Application for Communicating Dental Conditions.

The importance of visual aids in communicating clinical examination findings or proposed treatments in dentistry cannot be overstated. Similarly, communicating dental research results with tooth surface-level precision is impractical without visual representations. Here, we present the development, deployment, and two real-life applications of a web-based data visualization informatics pipeline that converts tooth surface-level information to colorized, three-dimensional renderings. The core of the informatics pipeline focuses on texture (UV) mapping of a pre-existing model of the human primary dentition. The 88 individually segmented tooth surfaces receive independent inputs that are represented in colors and textures according to customizable user specifications. The web implementation SculptorHD, deployed on the Google Cloud Platform, can accommodate manually entered or spreadsheet-formatted tooth surface data and allows the customization of color palettes and thresholds, as well as surface textures (e.g., condition-free, caries lesions, stainless steel, or ceramic crowns). Its current implementation enabled the visualization and interpretation of clinical early childhood caries (ECC) subtypes using latent class analysis-derived caries experience summary data. As a demonstration of its potential clinical utility, the tool was also used to simulate the restorative treatment presentation of a severe ECC case, including the use of stainless steel and ceramic crowns. We expect that this publicly available web-based tool can aid clinicians and investigators deliver precise, visual presentations of dental conditions and proposed treatments. The creation of rapidly adjustable lifelike dental models, integrated to existing electronic health records and responsive to new clinical findings or planned for future work, is likely to boost two-way communication between clinicians and their patients.

SAVE-T: Safety Analysis Visualization and Evaluation Tool

Traffic crashes are one of the biggest issues which constitute a threat to lives of the motorists and disrupt operations of the transportation system. To reduce the number of crashes and alleviate their impacts, it is necessary to scrutinize the factors contributing to the risk of traffic crashes. Lately, visual analytics tools become very popular for data exploration and obtaining insights from the data. In this paper, a new web-based data visualization tool called Safety Analysis Visualization and Evaluation Tool (SAVE-T) was introduced. This tool enables users to interactively create queries and visually explore the results. By utilizing an online crash database, it offers various innovative functionalities for analysis and visualization of the crash data such as custom query development module and a subway-like map for easily visualizing the accident on the roadway segments. This tool provides an effective and efficient way to transportation agencies and professionals for traffic safety analyses and visualizations.

Interactive web‐based data visualization with R, plotly, and shiny (Carson Sievert)

BiometricsVolume 77, Issue 2 p. 776-777 BOOK REVIEW Interactive web-based data visualization with R, plotly, and shiny (Carson Sievert) Ran Li, Ran Li Urban Health Collaborative, Drexel Dornsife School of Public Health, Philadelphia, Pennsylvania, USASearch for more papers by this authorUsama Bilal, Corresponding Author Usama Bilal ubilal@drexel.edu orcid.org/0000-0002-9868-7773 Urban Health Collaborative, Drexel Dornsife School of Public Health, Philadelphia, Pennsylvania, USA Department of Epidemiology and Biostatistics, Drexel Dornsife School of Public Health, Philadelphia, Pennsylvania, USA Correspondence Usama Bilal, MD MPH PhD, 3600 Market St. Suite 730, Philadelphia, PA 19104, USA. Email: ubilal@drexel.eduSearch for more papers by this author Ran Li, Ran Li Urban Health Collaborative, Drexel Dornsife School of Public Health, Philadelphia, Pennsylvania, USASearch for more papers by this authorUsama Bilal, Corresponding Author Usama Bilal ubilal@drexel.edu orcid.org/0000-0002-9868-7773 Urban Health Collaborative, Drexel Dornsife School of Public Health, Philadelphia, Pennsylvania, USA Department of Epidemiology and Biostatistics, Drexel Dornsife School of Public Health, Philadelphia, Pennsylvania, USA Correspondence Usama Bilal, MD MPH PhD, 3600 Market St. Suite 730, Philadelphia, PA 19104, USA. Email: ubilal@drexel.eduSearch for more papers by this author First published: 21 June 2021 https://doi.org/10.1111/biom.13474Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume77, Issue2June 2021Pages 776-777 RelatedInformation

Open-source web-based visualizer for dynamic-response shared taxi simulations

Abstract We describe a unique, web-based data visualization portal developed for use by researchers and public transit agencies investigating future shared-taxi fleet scenarios. Augmenting or even replacing fixed-route transit lines with automated, connected, shared taxi fleets may be a desirable alternative in less-densely developed areas. The MATSim agent-based transport microsimulation model is used to study scenarios including the status quo, dynamically-dispatched fleets with drivers, and fully autonomous fleets. This paper focuses on a data visualization portal which includes many interactive views such as agent (taxi) movements color-coded by number of passengers and trip request origins and destinations, changes in roadway and passenger volumes compared to a base case, and more. The agent-based simulation covers a 24 hour simulation period; analysts can hone in on specific times of day to examine, e.g. school pickup/drop-offs or commute trips connecting to rail stations. The tool is in operation for several small cities and rural regions in Germany and was successfully used as an outreach tool in public meetings. In addition, developers of the MATSim DRT extension found the visualizations particularly useful for debugging both the algorithms and the scenario definitions. The code is entirely open source and, while this specific study has a rather esoteric use case, the visualization platform has an extensible design that could be modified for other purposes.

Curating and Visualizing Dense Networks of Monsoon Precipitation Data: Integrating Computer Science Into Forward Looking Climate Services Development

Monsoon precipitation demonstrates a wide range of spatial and temporal variability in the U.S. Southwest. A variety of precipitation monitoring networks, including official networks, municipal flood control districts, and citizen science observers, can help improve our characterization and understanding of the monsoon. The data management challenges of integrating these diverse data sources can be formidable. Computer science and data management techniques provide a pathway for the design of forward looking climate services, especially those developed in collaboration with experts in this field. In this paper we present such a collaboration, integrating natural, social and computer science expertise. We document how we identified data networks and their sources and the computer science and data management workflow we employed to integrate and curate these data. We also present the web based data visualization tool and API that we developed as part of this process (monsoon.environment.arizona.edu). We use case study examples from the Tucson, AZ region to demonstrate the visualizer. We also discuss how this type of collaboration could be extended to existing or potential stakeholder collaborations, as we facilitate access to a curated set of data that gives an increasingly granular perspective on monsoon precipitation variability. We also discuss what this collaborative approach integrating natural, social and computer science perspectives can add to the evolution of climate services.

Interactive Web-Based Data Visualization with R, Plotly, and Shiny

Interactive Web-Based Data Visualization with R, Plotly, and Shiny

Open-Source Web-Based Visualizer for Dynamic-Response Shared Taxi Simulations

We describe a unique, web-based data visualization portal developed for use by researchers and public transit agencies investigating future shared-taxi fleet scenarios. Augmenting or even replacing fixed-route transit lines with automated, connected, shared taxi fleets may be a desirable alternative in less-densely developed areas. The MATSim agent-based transport microsimulation model is used to study scenarios including the status quo, dynamically-dispatched fleets with drivers, and fully autonomous fleets. This paper focuses on a data visualization portal which includes many interactive views such as agent (taxi) movements color-coded by number of passengers and trip request origins and destinations, changes in roadway and passenger volumes compared to a base case, and more. The agent-based simulation covers a 24 hour simulation period; analysts can hone in on specific times of day to examine, e.g. school pickup/drop-offs or commute trips connecting to rail stations. The tool is in operation for several small cities and rural regions in Germany and was successfully used as an outreach tool in public meetings. In addition, developers of the MATSim DRT extension found the visualizations particularly useful for debugging both the algorithms and the scenario definitions. The code is entirely open source and, while this specific study has a rather esoteric use case, the visualization platform has an extensible design that could be modified for other purposes.