Web-based Visualization Research Articles

Vitessce: integrative visualization of multimodal and spatially resolved single-cell data.

Multiomics technologies with single-cell and spatial resolution make it possible to measure thousands of features across millions of cells. However, visual analysis of high-dimensional transcriptomic, proteomic, genome-mapped and imaging data types simultaneously remains a challenge. Here we describe Vitessce, an interactive web-based visualization framework for exploration of multimodal and spatially resolved single-cell data. We demonstrate integrative visualization of millions of data points, including cell-type annotations, gene expression quantities, spatially resolved transcripts and cell segmentations, across multiple coordinated views. The open-source software is available at http://vitessce.io .

Web-based visualization of static and dynamic HD road traffic map layers

Web-based visualization of static and dynamic HD road traffic map layers

Developing a web-based visualization tool for solar energy awareness in Malaysia

Developing a web-based visualization tool for solar energy awareness in Malaysia

Identifying Legal, BIM Data and Visualization Requirements to Form Legal Spaces and Developing a Web-Based 3D Cadastre Prototype: A Case Study of Condominium Building

Over the past decade, numerous countries and researchers have been investigating the potential of 3D cadastre based on the Building Information Model (BIM). In Türkiye, the General Directorate of Land Registry and Cadastre (GDLRC) has been engaged in the “Production of 3D City Models and Creation of 3D Cadastral Bases Project” since 2018. One of the objectives is to develop 3D (physical) digital building models (and databases) through the digitization of floor plans of architectural drawings. In order to ensure the long-term viability of this project, a new regulation was issued in 2021. This regulation mandates the submission of 3D digital building models to the land registry in order to register condominiums. The future goals of the GDLRC include utilizing the 3D digital building models produced to create legal spaces in condominium buildings for the 3D cadastre. However, no research has yet been carried out for this goal. The objective of this research is to identify the legal and BIM data requirements for deriving legal spaces in condominium buildings, in light of the legislative analysis, and to develop a web-based 3D cadastre visualization prototype (showing both legal spaces and physical objects) based on the requirements obtained from the scientific literature. The result of this research demonstrates that well-structured and annotated BIM data can be used to develop a 3D cadastre prototype that meets the legal requirements in the case of Türkiye. Moreover, it is evident that, although the GDLRC has initiated the construction of a robust foundation for a 3D cadastre based on BIM, further enhancements and resolutions must be implemented from a legal and technical standpoint. It is postulated that the identified requirements and the proposed methodology in this research may assist decision-makers in Türkiye and globally in formulating their strategic plans for a 3D cadastre.

The initial structural health monitoring system of the Nibelungen Bridge Worms

As an essential part of the validation project for the German Research Foundation-funded Priority Program SPP 100+, an initial structural health monitoring system has been implemented on the Nibelungen Bridge in Worms. The aim of this system is to monitor the general behavior of the bridge for further development of condition indicators and to provide real data to all project partners to validate their methods. In this scope, 20 sensors, including radiation, humidity, temperature, inclination, linear variable differential transformer (LVDT), and acceleration sensors, have already been installed on the bridge. The quality of the recorded data, including measurement technical traceability, completeness, and reliability, shall be guaranteed. Subsequently, both the raw data and the first statistically evaluated values, such as the maximum, average, and minimum values, are saved. These raw and first-hand data are made available to the involved partners in a possible real-time manner. In addition, a web-based visualization platform has also been established. Therefore, users can access the deviation of the measured values from different sensors in the most direct way. The measured results of this initiated SHM system are compared and validated with numerical simulation results. Further supplementation of additional sensors, extension, and improvement of this initial system are aimed to be achieved in the future.

Tractometry of the Human Connectome Project: resources and insights.

The Human Connectome Project (HCP) has become a keystone dataset in human neuroscience, with a plethora of important applications in advancing brain imaging methods and an understanding of the human brain. We focused on tractometry of HCP diffusion-weighted MRI (dMRI) data. We used an open-source software library (pyAFQ; https://yeatmanlab.github.io/pyAFQ) to perform probabilistic tractography and delineate the major white matter pathways in the HCP subjects that have a complete dMRI acquisition (n = 1,041). We used diffusion kurtosis imaging (DKI) to model white matter microstructure in each voxel of the white matter, and extracted tract profiles of DKI-derived tissue properties along the length of the tracts. We explored the empirical properties of the data: first, we assessed the heritability of DKI tissue properties using the known genetic linkage of the large number of twin pairs sampled in HCP. Second, we tested the ability of tractometry to serve as the basis for predictive models of individual characteristics (e.g., age, crystallized/fluid intelligence, reading ability, etc.), compared to local connectome features. To facilitate the exploration of the dataset we created a new web-based visualization tool and use this tool to visualize the data in the HCP tractometry dataset. Finally, we used the HCP dataset as a test-bed for a new technological innovation: the TRX file-format for representation of dMRI-based streamlines. We released the processing outputs and tract profiles as a publicly available data resource through the AWS Open Data program's Open Neurodata repository. We found heritability as high as 0.9 for DKI-based metrics in some brain pathways. We also found that tractometry extracts as much useful information about individual differences as the local connectome method. We released a new web-based visualization tool for tractometry-"Tractoscope" (https://nrdg.github.io/tractoscope). We found that the TRX files require considerably less disk space-a crucial attribute for large datasets like HCP. In addition, TRX incorporates a specification for grouping streamlines, further simplifying tractometry analysis.

3D imaging application to the study of the early Neolithic ceramic complex: the decorated pottery of Rio Tana (Abruzzi, Italy)

This study aims to demonstrate the potential of 3D analysis in the study of prehistoric ceramic complexes. Due to the production systems used, prehistoric pottery decorations can vary significantly. Examining the frequency of various decorative methods used at different sites may help identify areas potentially connected to specific traditional elements. However, this is usually a cumbersome and time-consuming task. 3D digital methodologies can bring several advantages in the interpretation of ceramic decoration, providing new tools that can improve analytical skills, speed up the decision process, and support the researcher’s conclusions. This work focuses on the application of these methodologies to the study of decorated ceramics from the Neolithic site of Rio Tana (Abruzzo, central Italy): firstly, a pottery complex from this site has been 3D digitised; then, an interactive and web-based 3D visualisation system has been developed to enable access and study of these digital data. By comparing archaeological data with experimental data, in parallel with the analysis of 3D models’ surfaces, it has been possible to better define the technique employed and quickly identify the type of tool used to create the ceramic decorations. Furthermore, the web-based system made it possible to share and disseminate the digital dataset with the community, creating the conditions to make it easier to compare the frequency of different decoration methods and tools used at Rio Tana with other sites.

Content validation through expert judgement of web-based megalithic culture visualization

Content validation through expert judgement of web-based megalithic culture visualization

AMRViz enables seamless genomics analysis and visualization of antimicrobial resistance

We have developed AMRViz, a toolkit for analyzing, visualizing, and managing bacterial genomics samples. The toolkit is bundled with the current best practice analysis pipeline allowing researchers to perform comprehensive analysis of a collection of samples directly from raw sequencing data with a single command line. The analysis results in a report showing the genome structure, genome annotations, antibiotic resistance and virulence profile for each sample. The pan-genome of all samples of the collection is analyzed to identify core- and accessory-genes. Phylogenies of the whole genome as well as all gene clusters are also generated. The toolkit provides a web-based visualization dashboard allowing researchers to interactively examine various aspects of the analysis results. Availability: AMRViz is implemented in Python and NodeJS, and is publicly available under open source MIT license at https://github.com/amromics/amrviz.

Co-expression network analysis and identification of core genes in the interaction between wheat and Puccinia striiformis f. sp. tritici.

The epidemic of stripe rust, caused by the pathogenPuccinia striiformisf. sp.tritici(Pst), would reduce wheat (Triticum aestivum) yields seriously. Traditional experimental methods are difficult to discover the interaction between wheat and Pst. Multi-omics data analysis provides a new idea for efficiently mining the interactions between host and pathogen. We used 140 wheat-Pst RNA-Seq data to screen for differentially expressed genes (DEGs) between low susceptibility and high susceptibility samples, and carried out Gene Ontology (GO) enrichment analysis. Based on this, we constructed a gene co-expression network, identified the core genes and interacted gene pairs from the conservative modules. Finally, we checked the distribution of Nucleotide-binding and leucine-rich repeat (NLR) genes in the co-expression network and drew the wheat NLR gene co-expression network. In order to provide accessible information for related researchers, we built a web-based visualization platform to display the data. Based on the analysis, we found that resistance-related genes such as TaPR1, TaWRKY18 and HSP70 were highly expressed in the network. They were likely to be involved in the biological processes of Pst infecting wheat. This study can assist scholars in conducting studies on the pathogenesis and help to advance the investigation of wheat-Pst interaction patterns.

MortalityMinder: Visualization and AI Interpretations of Social Determinants of Premature Mortality in the United States

MortalityMinder enables healthcare researchers, providers, payers, and policy makers to gain actionable insights into where and why premature mortality rates due to all causes, cancer, cardiovascular disease, and deaths of despair rose between 2000 and 2017 for adults aged 25–64. MortalityMinder is designed as an open-source web-based visualization tool that enables interactive analysis and exploration of social, economic, and geographic factors associated with mortality at the county level. We provide case studies to illustrate how MortalityMinder finds interesting relationships between health determinants and deaths of despair. We also demonstrate how GPT-4 can help translate statistical results from MortalityMinder into actionable insights to improve population health. When combined with MortalityMinder results, GPT-4 provides hypotheses on why socio-economic risk factors are associated with mortality, how they might be causal, and what actions could be taken related to the risk factors to improve outcomes with supporting citations. We find that GPT-4 provided plausible and insightful answers about the relationship between social determinants and mortality. Our work is a first step towards enabling public health stakeholders to automatically discover and visualize relationships between social determinants of health and mortality based on available data and explain and transform these into meaningful results using artificial intelligence.

Modelling spatiotemporal variation in under-five malaria risk in Ghana in 2016–2021

BackgroundGhana is among the top 10 highest malaria burden countries, with about 20,000 children dying annually, 25% of which were under five years. This study aimed to produce interactive web-based disease spatial maps and identify the high-burden malaria districts in Ghana.MethodsThe study used 2016–2021 data extracted from the routine health service nationally representative and comprehensive District Health Information Management System II (DHIMS2) implemented by the Ghana Health Service. Bayesian geospatial modelling and interactive web-based spatial disease mapping methods were employed to quantify spatial variations and clustering in malaria risk across 260 districts. For each district, the study simultaneously mapped the observed malaria counts, district name, standardized incidence rate, and predicted relative risk and their associated standard errors using interactive web-based visualization methods.ResultsA total of 32,659,240 malaria cases were reported among children < 5 years from 2016 to 2021. For every 10% increase in the number of children, malaria risk increased by 0.039 (log-mean 0.95, 95% credible interval = − 13.82–15.73) and for every 10% increase in the number of males, malaria risk decreased by 0.075, albeit not statistically significant (log-mean − 1.82, 95% credible interval = − 16.59–12.95). The study found substantial spatial and temporal differences in malaria risk across the 260 districts. The predicted national relative risk was 1.25 (95% credible interval = 1.23, 1.27). The malaria risk is relatively the same over the entire year. However, a slightly higher relative risk was recorded in 2019 while in 2021, residing in Keta, Abuakwa South, Jomoro, Ahafo Ano South East, Tain, Nanumba North, and Tatale Sanguli districts was associated with the highest malaria risk ranging from a relative risk of 3.00 to 4.83. The district-level spatial patterns of malaria risks changed over time.ConclusionThis study identified high malaria risk districts in Ghana where urgent and targeted control efforts are required. Noticeable changes were also observed in malaria risk for certain districts over some periods in the study. The findings provide an effective, actionable tool to arm policymakers and programme managers in their efforts to reduce malaria risk and its associated morbidity and mortality in line with the Sustainable Development Goals (SDG) 3.2 for limited public health resource settings, where universal intervention across all districts is practically impossible.

Conceptual Design of a 3D Visualization Platform for Ships Based on Digital Twin Technology

Addressing the challenges in the current ship’s lifecycle design process, such as high difficulty in information sharing and complex installation of design environments, this study proposes a concept design of a ship 3D visualization platform based on digital twin technology. It constructs a web-based ship 3D visualization platform with an interactive interface of realism. The aim is to avoid cumbersome client-side programs and provide a method to showcase and interact with ship 3D models on web pages. This method not only reduces the threshold for ordinary users but also significantly enhances the work efficiency of professional designers. Following the model construction theory of digital twin platforms, it utilizes WebGL technology and the Three.js library to build ship 3D scenes, achieving ship 3D visualization. Functional interaction among modules is implemented using JavaScript, establishing the digital twin of the ship. Test results indicate that the proposed concept design of the ship 3D visualization platform can preliminarily fulfill the basic requirements of achieving ship 3D display, rendering, and interaction on web platforms. The proposed method can support the development of ship online collaborative design systems based on front-end internet technologies.

Strengthening health service delivery and governance through institutionalizing 'Urban Health Atlas'-A geo-referenced Information Communication and Technology tool: Lessons learned from an implementation research in three cities in Bangladesh.

Urban health governance in Bangladesh is complex as multiple actors are involved and no comprehensive data are currently available on infrastructure, services, or performance either in public and private sectors of the healthcare system. The Urban Health Atlas (UHA)-a novel and interactive geo-referenced, web-based visualization tool was developed in Bangladesh to provide geospatial and service information to decision makers involved in urban health service planning and governance. Our objective was to study the opportunities for institutionalization of the UHA into government health systems responsible for urban healthcare delivery and document the facilitators and barriers to its uptake. This implementation research was carried out during 2017-2019 in three cities in Bangladesh: Dhaka, Dinajpur and Jashore. During the intervention period, six hands-on trainings on UHA were provided to 67 urban health managers across three study sites. Thirty in-depth and twelve key informant interviews were conducted to understand user experience and document stakeholder perceptions of institutionalizing UHA. Capacity building on UHA enhanced understanding of health managers around its utility for service delivery planning, decision making and oversight. Findings from the IDIs and KIIs suggest that UHA uptake was challenged by inadequate ICT infrastructure, shortage of human resources and lack of ICT skill among managers. Motivating key decision makers and stakeholders about the potential of UHA and engaging them from its inception helped the institutionalization process. While uptake of UHA by government health managers appears possible with dedicated capacity building initiatives, its use and regular update are challenged by multiple factors at the implementation level. A clear understanding of context, actors and system readiness is foundational in determining whether the institutionalization of health ICTs is timely, realistic or relevant.

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.

METS-R SIM: A simulator for Multi-modal Energy-optimal Trip Scheduling in Real-time with shared autonomous electric vehicles

We develop an agent-based simulator named METS-R SIM to support operational decisions for multi-modal shared autonomous vehicle (SAEV) services. Compared with existing traffic simulators, METS-R SIM offers several valuable features including: 1) A microscopic vehicle movement model for SAEV services, which allows us to explicitly model vehicular interactions and generate detailed speed and acceleration profiles for energy estimation. 2) An efficient implementation in which parallel computing is embedded in METS-R SIM which can update the state of different agents (e.g., vehicle locations in different links) simultaneously. 3) A modular and extensible framework as the simulator is built upon an agent-based modeling environment named Repast Simphony which is featured by its well-factored abstractions; in addition, a server-client structure is introduced to implement real-time operational algorithms such as energy-efficient routing and adaptive transit scheduling. 4) Open-source, reproducible with web-based visualization (METS-R SIM introduces these features to promote transparency). We validate METS-R SIM by matching the aggregated travel time and travel distance with the real observed ones obtained from New York City (NYC). We also compare the generated speed profiles qualitatively to the ones reported in published studies. We demonstrate the functionalities of our simulator by simulating SAEV services deployed to serve travel needs related to three main transportation hubs in NYC.

Web-based visualization and rendering of aerial LiDAR point cloud for urban flood simulation

Purpose In an era overshadowed by the alarming consequences of climate change and the escalating peril of recurring floods for communities worldwide, the significance of proficient disaster risk management has reached unprecedented levels. The successful implementation of disaster risk management necessitates the ability to make informed decisions. To this end, the utilization of three-dimensional (3D) visualization and Web-based rendering offers decision-makers the opportunity to engage with interactive data representations. This study aims to focus on Thiruvananthapuram, India, where the analysis of flooding caused by the Karamana River aims to furnish valuable insights for facilitating well-informed decision-making in the realm of disaster management. Design/methodology/approach This work introduces a systematic procedure for evaluating the influence of flooding on 3D building models through the utilization of Web-based visualization and rendering techniques. To ensure precision, aerial light detection and ranging (LiDAR) data is used to generate accurate 3D building models in CityGML format, adhering to the standards set by the Open Geospatial Consortium. By using one-meter digital elevation models derived from LiDAR data, flood simulations are conducted to analyze flow patterns at different discharge levels. The integration of 3D building maps with geographic information system (GIS)-based vector maps and a flood risk map enables the assessment of the extent of inundation. To facilitate visualization and querying tasks, a Web-based graphical user interface (GUI) is developed. Findings The efficiency of comprehensive 3D building maps in evaluating flood consequences in Thiruvananthapuram has been established by the research. By merging with GIS-based vector maps and a flood risk map, it becomes possible to scrutinize the extent of inundation and the affected structures. Furthermore, the Web-based GUI facilitates interactive data exploration, visualization and querying, thereby assisting in decision-making. Originality/value The study introduces an innovative approach that merges LiDAR data, 3D building mapping, flood simulation and Web-based visualization, which can be advantageous for decision-makers in disaster risk management and may have practical use in various regions and urban areas.

VERB: Visualizing and Interpreting Bias Mitigation Techniques Geometrically for Word Representations

Word vector embeddings have been shown to contain and amplify biases in the data they are extracted from. Consequently, many techniques have been proposed to identify, mitigate, and attenuate these biases in word representations. In this article, we utilize interactive visualization to increase the interpretability and accessibility of a collection of state-of-the-art debiasing techniques. To aid this, we present the Visualization of Embedding Representations for deBiasing (VERB) system, an open-source web-based visualization tool that helps users gain a technical understanding and visual intuition of the inner workings of debiasing techniques, with a focus on their geometric properties. In particular, VERB offers easy-to-follow examples that explore the effects of these debiasing techniques on the geometry of high-dimensional word vectors. To help understand how various debiasing techniques change the underlying geometry, VERB decomposes each technique into interpretable sequences of primitive transformations and highlights their effect on the word vectors using dimensionality reduction and interactive visual exploration. VERB is designed to target natural language processing (NLP) practitioners who are designing decision-making systems on top of word embeddings and researchers working with the fairness and ethics of machine learning systems in NLP. It can also serve as a visual medium for education, which helps an NLP novice understand and mitigate biases in word embeddings.

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.

The Urban Toolkit: A Grammar-Based Framework for Urban Visual Analytics.

While cities around the world are looking for smart ways to use new advances in data collection, management, and analysis to address their problems, the complex nature of urban issues and the overwhelming amount of available data have posed significant challenges in translating these efforts into actionable insights. In the past few years, urban visual analytics tools have significantly helped tackle these challenges. When analyzing a feature of interest, an urban expert must transform, integrate, and visualize different thematic (e.g., sunlight access, demographic) and physical (e.g., buildings, street networks) data layers, oftentimes across multiple spatial and temporal scales. However, integrating and analyzing these layers require expertise in different fields, increasing development time and effort. This makes the entire visual data exploration and system implementation difficult for programmers and also sets a high entry barrier for urban experts outside of computer science. With this in mind, in this paper, we present the Urban Toolkit (UTK), a flexible and extensible visualization framework that enables the easy authoring of web-based visualizations through a new high-level grammar specifically built with common urban use cases in mind. In order to facilitate the integration and visualization of different urban data, we also propose the concept of knots to merge thematic and physical urban layers. We evaluate our approach through use cases and a series of interviews with experts and practitioners from different domains, including urban accessibility, urban planning, architecture, and climate science. UTK is available at urbantk.org.