Data Visualization System Research Articles

Addressing Information Consumer Experience through a User-Centered Information Management System in a Chilean University

Prior research on the successful design and construction of data visualization systems or information management systems has not fully taken into account the holistic experience of employees working with information within the organization but has centered on specific aspects, such as user experience or data quality, attempting to go against information management quality, as those approaches can significantly influence users’ perceptions and their motivation to effectively use such tools for decision making. This study addresses the information consumer experience (ICX) in a Chilean Higher Education institution through the design and implementation of an user-centric centralized information management system. This system was created using an adapted design thinking methodology with an ICX perspective to identify and integrate the information consumers’ demands and other factors correlated with ICX into the system’s design. The proposed system is a technological extension of an information resource validation process that involves senior data analysts from the Analytics Department and external data analysts from other departments across the organization. This process helps to address data quality and information management quality (IMQ) problems of the organization, representing a centralized data source for all information consumers into the organization, offering consistent, accessible, and good quality data to address daily work and enhance information consumers experience, and managerial work.

Data Fusion for Smart Civil Infrastructure Management: A Conceptual Digital Twin Framework

Effective civil infrastructure management necessitates the utilization of timely data across the entire asset lifecycle for condition assessment and predictive maintenance. A notable gap in current predictive maintenance practices is the reliance on single-source data instead of heterogeneous data, decreasing data accuracy, reliability, adaptability, and further effectiveness of engineering decision-making. Data fusion is thus demanded to transform low-dimensional decisions from individual sensors into high-dimensional ones for decision optimization. In this context, digital twin (DT) technology is set to revolutionize the civil infrastructure industry by facilitating real-time data processing and informed decision-making. However, data-driven smart civil infrastructure management using DT is not yet achieved, especially in terms of data fusion. This paper aims to establish a conceptual framework for harnessing DT technology with data fusion to ensure the efficiency of civil infrastructures throughout their lifecycle. To achieve this objective, a systematic review of 105 papers was conducted to thematically analyze data fusion approaches and DT frameworks for civil infrastructure management, including their applications, core DT technologies, and challenges. Several gaps are identified, such as the difficulty in data integration due to data heterogeneity, seamless interoperability, difficulties associated with data quality, maintaining the semantic features of big data, technological limitations, and complexities with algorithm selection. Given these challenges, this research proposed a framework emphasizing multilayer data fusion, the integration of open building information modeling (openBIM) and geographic information system (GIS) for immersive visualization and stakeholder engagement, and the adoption of extended industry foundation classes (IFC) for data integration throughout the asset lifecycle.

Managing andmonitoring a pandemic: showcasing a practical approach forthe genomic surveillance ofSARS-CoV-2.

With the rapidly growing amount of biological data, powerful but also flexible data management and visualization systems are of increasingly crucial importance. The COVID-19 pandemic has more than highlighted this need and the challenges scientists are facing. Here, we provide an example and a step-by-step template for non-IT personnel to easily implement an intuitive, interactive data management solution to manage and visualize the high influx of biological samples and associated metadata in a laboratory setting. Our approach is illustrated with the genomic surveillance for SARS-CoV-2 in Germany, covering over 11 600 internal and 130 000 external samples from multiple datasets. We compare three data management options used in laboratories: (i) simple, yet error-prone and inefficient spreadsheets, (ii) complex and long-to-implement laboratory information management systems and (iii) high-performance database management systems. We highlight the advantages and pitfalls of each option and outline why a document-oriented NoSQL option via MongoDB Atlas can be a suitable solution for many labs. Our example can be treated as a template and easily adapted to allow scientists to focus on their core work and not on complex data administration.

RANCANG BANGUN SISTEM INFORMASI PENGELOLAAN WISATA PULAU RANOH BERBASIS WEBSITE

The purpose of making the Design and Development of a Website-Based Ranoh Island Tourism Management Information System is to promote and facilitate booking of tour packages on Ranoh Island. Web-based visual information system is a system consisting of text and graphic images. It is these factors that make these tours interesting and make bookings easy. In addition, the Website-Based Ranoh Island Tourism Management Information System is a system that contains complete information for tourists and can be found at any time. This support cannot be separated from the research process design and technology. This study aims to design a Website-Based Ranoh Island Tourism Management Information System as a source of information for viewing and ordering tourist attractions and other facilities on Ranoh Island. The Website-Based Ranoh Island Tourism Management Information System was developed using the PHP programming language and data stored in a database using MySQL to optimize system and database performance. The Google Maps API is one of the features of this information system that can be used to add maps to websites using JavaScript. The result of the design is a web tourism information system which should be a way to promote tourism in the city of Batam, so that through this web design it is hoped that there will be a similar system to create better services. and more complete than existing services.

Data Visualization Based On Sentiment Analysis to Identify the Quality of Internet Service Providers in Malaysia

Nowadays, most of the people have subscribed to their own internet service providers. However, due to slow of speed, connectivity, quality, and customer satisfaction need a proper evaluation. In addition, the rate of internet adoption is still slow. This project aims to develop a web-based system of data visualization based on sentiment analysis of internet service providers in Malaysia. For the project methodology is conducted in three phases, which include studying the existing problem of the internet service providers in Malaysia, developing a web-based system of data visualization based on sentiment analysis, and the evaluation of the usability of the system. The System Development Life Cycle (SDLC) has been used in this project which are analysis, design, implementation, testing, maintenance, and usability. The quality of internet services is a crucial factor in determining the satisfaction of customers in the telecommunications industry. The data visualization system based on sentiment analysis can assist customers in making informed decisions when choosing the right Internet Service Provider (ISP) by providing a better understanding of the quality of internet services offered by different ISPs. The sentiment analysis approach also done by using the corpus-based approach. The evaluation of the usability result was done by 3 experts through questionnaires using the linear scale indicator to evaluate the usability of the system. The visualization of data is important which can help the user understand the information in detail.

The Implementation of Bantu Warga Apps and Metabase for Spatial Data Processing In Surabaya

Civil registration and vital statistics (CRVS) is known as an essential supporting system for effective policy-making and service delivery. Its primary purpose is establishing an individual's legal identity and vital events to ensure all citizens get their rights well. Furthermore, an advanced level of CRVS is equipped with a forecasting system to serve more useful data. This paper discusses the potential benefits and challenges of using Metabase and Bantu Warga as civil ministry support systems. The spatial data visualization system using open-source Metabase ran well and resulted in many visualization geospatial maps like birth, marriage and divorce, education, and employment. The forecasting autoregression model configuration and cumulative sum dataset reach the best error result in 1056618. The other aspects, like the self-isolation management system, civil documents classification system, and OCR system, have a good result.

Tracking emergency response actions during COVID-19 leads to development of an innovative public health evaluation tool

SettingEarly in the pandemic, KFL&A Public Health needed a way to capture, organize, and display COVID-19-related events to be accountable for and evaluate our actions.InterventionWe used accessible software (Microsoft Office 365 suite, Microsoft PowerBI) to develop a data collection and visualization system. The Canadian Institute for Health Information (CIHI) developed a timeline and categorization approach for provincial and national COVID-related interventions, which was used to develop a regional version for local events using similar categories. We collected and displayed qualitative data alongside epidemiological data that allowed users to display different timelines of actions and outcomes and evaluate our response.OutcomesIn developing the timeline, we took stock of the information and data we wanted to collect, sort, and display locally. Next, we collected information on response actions, case and contact tracing, and staffing changes in a database that we displayed on a timeline. We included CIHI’s data set to provide insight into pandemic response across all jurisdictions.ImplicationsOur timeline tool has many advantages for public health authorities beyond responding to a rapidly evolving emergency. By collecting information on events as they occur, decisions and actions are documented that may otherwise be overlooked. This enables decision-makers to visualize the impact of public health actions on health outcomes over time. The tool is completely customizable and scalable depending on the project scope and we plan to apply this method to other public health programming. Finally, we include lessons learned from quickly developing these tools in a real-time pandemic setting, both locally at KFL&A Public Health and nationally at CIHI.

Python-based Epidemic Data Visualization System

In order for people to timely understand the relevant dynamics of the epidemic and do their own protection, the epidemic data visualization system has been developed and designed. Based on Python language and Echarts visualization technology, the obtained epidemy-related data are visually classified and displayed, so that the data is more clearly displayed in front of users, providing users with a relatively comprehensive channel to obtain epidemic information.

Methods and tools for information visualization on the basis of attributed hierarchical graphs with ports

At present visualization of graph models is an inherent part of the processing of complex information about the structure of objects, systems and processes in many applications in science and technology, and at the market there are widely presented science-intensive software products, using the information visualization on the basis of graph models. Since the information that it is desirable to visualize is constantly growing and becoming more complex, more and more situations arise in which classical graph models cease to be adequate. More powerful graph-theoretic formalisms are required and appear to represent information models with a hierarchical structure, since hierarchy is the basis of numerous methods for visual processing of complex big data in various fields of application. One of these formalisms is the so-called hierarchical graphs. This formalism allows selecting in the given classical graph a set of such its parts (so-called fragments) that all elements of each selected fragment deserve separate joint consideration, and all fragments of the selected set form a nesting hierarchy. At the A. P. Ershov Institute of Informatics Systems constructed the Visual Graph visualization system, which is based on hierarchical graphs and allows exploring complex structured big data through their visual representations. In many applications, objects modeled by graph vertices are complex and contain non-intersecting logical parts (so-called ports) through which these objects are in a relationship modeled by arcs. In the paper the formalism of attributed hierarchical graphs with ports is introduced and new possibilities of the Visual Graph system for visualization of large structured data based on attributed hierarchical graphs with ports are considered.

Spatial and Temporal Data Visualisation for Mass Dissemination: Advances in the Era of COVID-19.

The COVID-19 pandemic is the first major pandemic of the digital age and has been characterised by unprecedented public consumption of spatial and temporal disease data, which can enable greater transparency and accountability of governments to the public for their public health decisions. A variety of state and non-state actors have collated and presented maps, charts, and plots of data related to the pandemic in both static and dynamic formats. In particular, there has been a proliferation of online dashboards presenting data related to the pandemic. The sources and types of information displayed have evolved rapidly during the pandemic, with a general trend towards providing more specialised information pertinent to specific aspects of epidemiology or disease control, as opposed simply to disease and death notifications. Limited evaluation of the quality of COVID-19 data visualisation tools has been conducted and significant effort now needs to be spent on standardisation and quality improvement of national and international data visualisation systems including developing common indicators, data quality assurance mechanisms and visualisation approaches, and building compatible electronic systems for data collection and sharing. The increasing availability of disease data for public consumption presents challenges and opportunities for government, media organisations, academic research institutions, and the general public. A key challenge is ensuring consistency and effectiveness of public health messaging to ensure a coordinated response and public trust in intervention strategies. Capitalising on opportunities for greater government accountability for public health decision-making, and more effective mobilisation of public health interventions, is predicated on the provision of accurate and timely information.

Machine learning and mixed reality for smart aviation: Applications and challenges

The aviation industry is a dynamic and ever-evolving sector. As technology advances and becomes more sophisticated, the aviation industry must keep up with the changing trends. While some airlines have made investments in machine learning and mixed reality technologies, the vast majority of regional airlines continue to rely on inefficient strategies and lack digital applications. This paper investigates the state-of-the-art applications that integrate machine learning and mixed reality into the aviation industry. Smart aerospace engineering design, manufacturing, testing, and services are being explored to increase operator productivity. Autonomous systems, self-service systems, and data visualization systems are being researched to enhance passenger experience. This paper investigate safety, environmental, technological, cost, security, capacity, and regulatory challenges of smart aviation, as well as potential solutions to ensure future quality, reliability, and efficiency.

Study and Development of IOT based Smart Irrigation System using Soil Moisture and Weather Prediction

Abstract: The smart irrigation system was developed to optimize water use of crops. The system has a distributed wireless network of soil-moisture temperature sensors placed in the root zone of the plants. Also, a gateway unit handles sensor information, triggers, actuators, and transmits data to the web application. The intelligence of The proposed system is based on a smart algorithm, which considers sensed data along with the weather forecast parameters like precipitation, air temperature, humidity, and UV for the near future. The complete system has been developed and deployed on a pilot scale, where the sensor node data is wirelessly collected over the cloud using web- services and a web-based information visualization and decision support system provides real-time information insights based on the analysis of sensor dataand weather forecast data. The paper describes the system and discusses in detail the information processing results of three weeks data based on the proposed algorithm. The system is fully functional and the prediction results are very encouraging

Spatial Analysis of Poverty Incidence and Road Networks in Eastern Visayas Region, Philippines

Poverty is a prevailing challenge in the Philippines. Through the small area estimation (SAE) of the Philippine Statistics Authority, the poor cities and municipalities with poor households were identified. Some locations are also vulnerable to natural calamities and have limited resources. The 2018 SAE shows that the region of Eastern Visayas is one of the poorest in the country. Moreover, the region is vulnerable to natural hazards, particularly typhoons. The regional road network is also less connected for the poorer municipalities. Hence, slow economic growth is a concerted outcome. To provide an evidence-based framework on potentially optimized resource allocation of, say, government institutions and humanitarian organizations in countering these poverty concerns exacerbated by natural calamities, this paper used the geographical information system (GIS) for easier visualization and interpretability. Spatial analyses were also applied to [1] determine if clusters of poverty exist in the region across different periods and [2] if hot spots of poverty incidence exist in the latest SAE. The findings reveal that poverty incidence for all four previous periods of SAE has significant non-random clusters. In addition, poverty hot spots, at varying confidence levels, were statistically identified. These hot spots are also vulnerable to frequent typhoons and have limited access to national roads. Additionally, the bootstrap regression shows that economic growth could be boosted by expanding road networks as an indicator of decreased poverty incidence. This study, thus, further emphasizes the importance of data-driven decision-making, particularly in efforts to counter poverty, including some of its aggravating external factors such as natural calamities. The application of empirical methods in formulating and improving policies, especially those related to infrastructure investments and expansions, is also recommended, given the limited resources. It also highlights how road networks in the region could be instrumental in promoting economic progress, particularly in less accessible areas.

Retraction

Retraction: Li J, Hu B. Sparse data inspired depth of urbanization in Zhejiang based on geographic information system and visual system. J Concurrency Computat Pract Exper. 2021; 33(12).The above article, published online on 27 Feb 2020 Wiley Online Library (https://onlinelibrary.wiley.com/doi/full/10.1002/cpe.5704) has been retracted by agreement between the journal Editor, Professor David W. Walker, School of Computer Science and Informatics, Cardiff University, Cardiff CF24 3AA, UK and Wiley Periodicals, LLC. The retraction has been agreed following an investigation based on allegations raised by a third party. Several inconsistencies were found, including general logical flaws and irrelevant citations, making the motivation and conclusion of the article untrustworthy. The editorial office did not receive a response from the authors, and so requested underlying experimental data was not available for evaluation. Accordingly, the editors consider the conclusions of this manuscript invalid.

A solution for creating dynamic networks of symptoms in cognitive-behavioral functional analysis and therapy – participatory design protocol

PurposeOne of the recommendations in process-based cognitive therapies suggests that functional analysis created by the clinician should be supported by empirical data collected through daily sampling. It enables the computing of a dynamic network of psychological processes and symptoms supporting clinical decisions but also therapeutic progress monitoring. However, the experience sampling solutions available in the market do not enable the automatic creation of this kind of network; thus, the use of this approach in clinical practice is practically impossible without advanced statistical skills and significant time investment. The purpose of the present paper is to describes a protocol of a research project based on a participatory approach aiming to create a solution enabling therapists not only to set up a personalized daily sampling for their patients and collect the data but also providing a fully automated visualization of the network adapted for therapeutic purposes.Design/methodology/approachThe project will require creating a platform for therapists where they can set up monitoring and receive dynamic networks visualization, creating an experience sampling application for patients connected to the platform and creating an optimal data visualization system that will enable therapists to accurately and quickly interpret the network. A series of participatory workshops, qualitative and quantitative studies are described.FindingsThe presented studies will enable us to evaluate the ergonomy of use of both platform and app in laboratory and ecological settings along with the evaluation of network interpretation accuracy.Originality/valueTo the best of the authors’ knowledge, this is the first participatory design protocol for creating a solution that might enable clinicians to use a dynamic network approach in their everyday clinical practice. The challenges and opportunities of creating this kind of mHealth solution are discussed.

HyperCube4x: Exploring and Analyzing Data in Virtual Reality Using HyperRelational and HyperAnalyzer

Hypercube is a novel viewport management and information visualization system proposal that introduces three applications (called WorkScenes), focusing on interaction, immersive reading, data exploration, analysis, and visualization concepts. After presenting the conceptual description, interaction metaphors, and the prototype in a previous publication, this article presents HyperRelational and HyperAnalyzer, the WorkScenes focused on multidimensional data exploration, analysis, and visualization. First, the manuscript explores previous work on Human-Computer Interaction-related disciplines, such as cognitive psychology, cognitive engineering, and neuroscience. Then, we introduce HyperRelational and HyperAnalyzer, focusing on their fundamental concepts 1) Geometrical visualization; 2) mapping relationships among information as spatial dimensions. Also, the Screenshots help illustrate the mentioned concepts. Finally, the “Results and Discussion” section demonstrates how these features integrate with the flow, presence, and immersion of Virtual Reality, fit Shneiderman’s visual-information-seeking mantra and solve some desktop metaphor-related issues. Additionally, we present test results conducted with 26 participants that show an acceptability rate of 74% amongst users and highlight their positive feedback/experience regarding HyperAnalyzer. On the other hand, the System Usability Scale (SUS) evaluation scored 60.6731. The score demonstrates that HyperAnalyser scored a little better than Microsoft Excel. Therefore, we conclude that the concepts presented here are viable, but it is still necessary to evolve usability to make HyperCube commercially viable.

AUGMENTED REALITY BASED INFORMATION TECHNOLOGY FOR OBJECTS 3D MODELS VISUALIZATION

At the current stage of IT industry development, augmented reality is of interest both from the side of science and from the business side, since it is an advanced and newest tool for introducing a new immersive user experience. Today there are plenty ready-to-use applications that use AR for business, educational, medical and other purposes. Augmented Reality is currently one of the most popular upcoming technologies most commonly known for its use within games and advertising. By combining three-dimensional modelling with augmented reality, it could be possible to obtain new user friendly applications for the representing 3D models of objects in real time and in real size. The topic of research in the field of augmented reality is currently relevant both for science and for the business industry. The paper proposes a multifunctional information system for three-dimensional models visualization in augmented reality, which is implemented in the form of a cross-platform mobile application. The proposed information system uses a device camera as a mean of object visualization and provides quick reproduction of the selected from the application`s database model in augmented reality in real size and in real time. The developed application works quite well, has a user friendly and intuitive interface and allows user to add own models, that makes this tool multipurpose.Test 3D models have been created for conducting experiments for verification the proposed information system operation. The further efforts of the authors will be directed to improving the existing algorithms for extending the current functionality of the proposed tool for 3D objects models visualization in augmented reality and application of the developed tool for real-life needs, such as digitization and visualization of museum exhibits and archaeological artifacts of Khmelnytskyi region.

Smart Irrigation and Crop Health Prediction

The scarcity of clean water resources around the globe has generated a need for their optimum utilization Internet of Things (IoT) solutions, based on the application specific sensors’ data acquisition and intelligent processing are bridging the gaps between the cyber and physical world. IoT based smart irrigation systems can help in achieving optimum water-resource utilization in the precision farming landscape. This paper presents an open-source technology based smart system to predict the irrigation requirements of a field using the sensing of ground parameter like soil moisture soil temperature, and environmental conditions along with the weather forecast data from the Internet. The intelligence of the proposed system is based on a smart algorithm, which considers sensed data along with the weather forecast parameters like precipitation, air temperature, humidity, and UV for the near future. The complete system has been developed and deployed on a pilot scale, where the sensor node data is wirelessly collected over the cloud using web-services and a web-based information visualization and decision support system provides the real-time information-insights based on the analysis of sensors data and weather forecast data. The paper describes the system and discusses in detail the information processing results of three weeks data based on the proposed algorithm. The system is fully functional and the prediction results are very encouraging.

Multi-View Analysis of High-Resolution Geomorphic Features in Complex Mountains Based on UAV–LiDAR and SfM–MVS: A Case Study of the Northern Pit Rim Structure of the Mountains of Lufeng, China

Unmanned aerial vehicles (UAVs) and light detection and ranging (LiDAR) can be used to analyze the geomorphic features in complex plateau mountains. Accordingly, a UAV–LiDAR system was adopted in this study to acquire images and lidar point-cloud dataset in the annular structure of Lufeng, Yunnan. A three-dimensional (3D) model was constructed based on structure from motion and multi-view stereo (SfM–MVS) in combination with a high-resolution digital elevation model (DEM). Geomorphic identification, measurement, and analysis were conducted using integrated visual interpretation, DEM visualization, and geographic information system (GIS) topographic feature extraction. The results indicated that the 3D geomorphological visualization and mapping were based on DEM, which was employed to identify the dividing lines and ridges that were delineated of the pit rim structure. The high-resolution DEM retained more geomorphic detail information, and the topography and the variation between ridges were analyzed in depth. The catchment and ponding areas were analyzed using accurate morphological parameters through a multi-angle 3D visualization. The slope, aspect, and topographic wetness index (TWI) parameters were analyzed through mathematical statistics to qualitatively and accurately analyze the differences between different ridges. This study highlighted the significance of the UAV–LiDAR high-resolution topographic measurements and the SfM–MVS 3D scene modelling in accurately identifying geomorphological features and conducting refined analysis. An effective framework was established to acquire high-precision topographic datasets and to analyze geomorphological features in complex mountain areas, which was beneficial in deepening the research on numerical simulation analysis of geomorphological features and reveal the process evolution mechanism.

Using Industry-based Spatio-Temporal Database to Store and Retrieve Big Trafc Data

This paper deals with the storage, processing and retrieval of large amounts of vehicle movement data from spatio-temporal database. The objective is to provide information about the solutions that are available for effective storage, data retrieval, and visualization of spatio-temporal data, as well as details on how to use those data to develop applications. The specific industry-based spatio-temporal database called SpaceTime provided by Mireo d.d. was used as a base for the development of an effective system for data processing, visualization, transmission and storage. The paper presents the architecture, as well as implementation details to implement such a system. The results indicate that SpaceTime database with its specific architecture and indexing method, outperforms other freely available database management systems dealing with spatio-temporal data.