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The practice of review writing is an essential component of postgraduate students' academic studies for graduation requirement and especially for those who are undergoing their postgraduate studies by theses by publication. However, very few studies have focused on review genres. In this review, the researchers would like to offer an overview of different types of review articles and identify the trend in the development of the review article genre. The researchers of this study employed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. They identified the published articles specific to the review genres via a structured keyword search in Web of Science, Scopus, and Google Scholar (from the years 2019–2022). A mixed analysis approach (e.g., qualitative analysis combined with quantitative analysis) was conducted to further examine the selected articles using the data visualization software CiteSpace. The results showcased that there were currently a limited number of review types in social science disciplines. The researchers call for more effort to discover new models for writing review genres in the EFL/ESL context. This study also discusses the theoretical and practical implications. [ABSTRACT FROM AUTHOR]

The article discusses the implementation of the Spartan Experience Record (SER) at Michigan State University (MSU), which provides undergraduate students with a formal record of their co-curricular learning accomplishments. The SER aims to create a comprehensive dataset on what students learn in these co-curricular opportunities. To make the data more accessible, data visualization dashboards were created. The article offers key considerations for building data visualizations that support student learning outcomes and assessment goals. The challenges of customization in creating the dashboards are also discussed. Overall, the SER and data visualizations contribute to tracking and understanding the impact of co-curricular engagement on student success. [Extracted from the article]

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Background: This paper introduces DynamoVis version 1.0, an open-source software developed to design, record and export custom animations and multivariate visualizations from movement data, enabling visual exploration and communication of patterns capturing the associations between animals' movement and its affecting internal and external factors. Proper representation of these dependencies grounded on cartographic principles and intuitive visual forms can facilitate scientific discovery, decision-making, collaborations, and foster understanding of movement. Results: DynamoVis offers a visualization platform that is accessible and easily usable for scientists and general public without a need for prior experience with data visualization or programming. The intuitive design focuses on a simple interface to apply cartographic techniques, giving ecologists of all backgrounds the power to visualize and communicate complex movement patterns. Conclusions: DynamoVis 1.0 offers a flexible platform to quickly and easily visualize and animate animal tracks to uncover hidden patterns captured in the data, and explore the effects of internal and external factors on their movement path choices and motion capacities. Hence, DynamoVis can be used as a powerful communicative and hypothesis generation tool for scientific discovery and decision-making through visual reasoning. The visual products can be used as a research and pedagogical tool in movement ecology. [ABSTRACT FROM AUTHOR]

The Grand Challenges in Assessment in Higher Education project seeks to address three significant ongoing challenges faced by assessment professionals (Singer-Freeman and Robinson 2020a; 2020b). Data storytelling shares data with stakeholders through a narrative format that answers the "who, what, where, why, and how" encapsulated in the data. The culture of assessment then became an opportunity to use data for with can experience a transformational moment when assessment data is understood as data I about i student learning that can lead to discovering I how i students learn. [Extracted from the article]

"Doing economics" is an important theme of undergraduate economics programs. Capstone courses increasingly include instruction in "data literacy" and the STEM-related skills of quantitative and empirical methods. Because the professional discipline has moved in this direction and because of greater employer demand for these skills, data visualization is a key component of data literacy. Tableau is a free data visualization software widely used in the data analytics industry. In this article, the authors introduce an exercise that teaches the fundamental Tableau concepts and commands needed to create charts, assemble them in a dashboard, and tell a story of patterns observed in the data. The exercise assumes no prior experience in Tableau and is appropriate for undergraduate upper-level economics courses or an empirical methods course. [ABSTRACT FROM AUTHOR]

We present a case for teaching data analytics skills in auditing classes using the data visualization software Tableau. We use the Tableau-embedded data file "US Superstore," which we edited to include cash receipts and discounts to provide a complete order to cash cycle. Students learn how to create data visualizations and dashboards, and how to apply them to audit-planning considerations. Students then perform substantive testing of the revenue (order to cash) cycle and identify issues in the data that relate to revenue. We propose that this case material can be tailored by instructors to fit their particular needs and course curriculum. This case provides students with hands-on exposure to data analytic and visualization capabilities. Student feedback was very favorable and student comments indicated that the case was practical, realistic, and informative, and provided them a better understanding of data visualization. Data Availability: For data availability, please contact the corresponding author. [ABSTRACT FROM AUTHOR]

Data visualization has a critical role in the advancement of modern data analytics. Visualization lends assurances to data validity and completeness, as well as to the effectiveness of cleaning and aggregation tactics. It provides the means by which to explore and discover relationships otherwise hidden from default assumptions in statistical modeling. Strong visualization is also fundamental to end-result conveyance and audience interpretation. But how can one ensure that strength? How can one avoid developing representations that are marginal in value, or worse misleading? In this paper, I will discuss theory, evidence, and practical approaches to managing data visualization development, viewing data visualization not simply as an outcome but as a continuous process and facet of organizational culture. [ABSTRACT FROM AUTHOR]

For irregularly measured time-series data, the measurement frequency or interval is as crucial information as measurements are. A well-known time-series visualization such as the line graph is good at showing an overall temporal pattern of change; however, it is not so effective in revealing the measurement frequency/interval while likely giving illusory confidence in values between measurements. In contrast, the bar graph is more effective in showing the frequency/interval, but less effective in showing an overall pattern than the line graph. We integrate the line graph and bar graph in a unified visualization model, called a ripple graph, to take the benefits of both of them with enhanced graphical integrity. Based on the ripple graph, we implemented an interactive time-series data visualization tool, called Stroscope, which facilitates multi-scale visualizations by providing users with a graphical widget to interactively control the integrated visualization model. We evaluated the visualization model (i.e., the ripple graph) through a controlled user study and Stroscope through long-term case studies with neurologists exploring large blood pressure measurement data of stroke patients. Results from our evaluations demonstrate that the ripple graph outperforms existing time-series visualizations, and that Stroscope has the efficacy and potential as an effective visual analysis tool for (irregularly) measured time-series data. [ABSTRACT FROM AUTHOR]

The article describes the use of the Web 3.0 technology by first-year undergraduates to create concept maps. It notes that use of the data-visualization application, Popplet, and Web 3.0 in creating the maps from the official papers of a former member of the U.S. Congress, which allow instructors to illustrate information's complex structures. It highlights that the research draws students from library archival studies and political science and Web 3.0 help them develop their research skills.

The article focuses on security issues that have arisen by scientists regarding the handling of big data. It states that faster databases, higher-speed bus systems and data visualization software are enable to extract information from big analog data (BAD). It mentions tools related to security systems such as the SWIR light, which is useful in navigation and security, and a digital micromirror device (DMD) along with the theory of compressive sampling (CS) in big data handling.

Recently, we reported obtaining tomograms of meibomian glands from healthy volunteers using commercial anterior segment optical coherence tomography (AS-OCT), which is widely employed in clinics for examination of the anterior segment. However, we could not create 3D images of the meibomian glands, because the commercial OCT does not have a 3D reconstruction function. In this study we report the creation of 3D images of the meibomian glands by reconstructing the tomograms of these glands using high speed Fourier-Domain OCT (FD-OCT) developed in our laboratory. This research was jointly undertaken at the Department of Ophthalmology, Seoul St. Mary's Hospital (Seoul, Korea) and the Advanced Photonics Research Institute of Gwangju Institute of Science and Technology (Gwangju, Korea) with two healthy volunteers and seven patients with meibomian gland dysfunction. A real time imaging FD-OCT system based on a high-speed wavelength swept laser was developed that had a spectral bandwidth of 100 nm at the 1310 nm center wavelength. The axial resolution was 5 µm and the lateral resolution was 13 µm in air. Using this device, the meibomian glands of nine subjects were examined. A series of tomograms from the upper eyelid measuring 5 mm (from left to right, B-scan) × 2 mm (from upper part to lower part, C-scan) were collected. Three-D images of the meibomian glands were then reconstructed using 3D “data visualization, analysis, and modeling software”. Established infrared meibography was also performed for comparison. The 3D images of healthy subjects clearly showed the meibomian glands, which looked similar to bunches of grapes. These results were consistent with previous infrared meibography results. The meibomian glands were parallel to each other, and the saccular acini were clearly visible. Here we report the successful production of 3D images of human meibomian glands by reconstructing tomograms of these glands with high speed FD-OCT. [ABSTRACT FROM AUTHOR]

The article discusses the tools that made up Cal-Adapt to help people visualize and understand the changes that are projected to affect California. The tools include the Local Fact Sheet, Map animations and data visualization. It provides detailed discussion concerning the utilization of the said tools. It also highlights the significance of giving users the ability to see how the said changes may look in different locations.

The SuperCDMS experiment (Super Cryogenic Dark Matter Search) searches for low-mass dark matter and will be located approximately 2 km deep underground in the Sudbury Neutrino Observatory (SNOLAB, Canada). The planned kilogram scale detector payload is a mix of germanium and silicon detectors placed in four towers. The data acquisition (DAQ) will contain Detector Control and Readout Cards (DCRCs) connected to detectors and a flexible triggering scheme containing hardware and software triggers. Slow control, environmental monitoring and data quality checking will be integrated into the experimental framework. The near-to-live data quality system enables high experimental efficiency. Data visualization software is being developed for the data quality system. The SuperCDMS experiment, its detector payload and data acquisition system, will be discussed in the presentation. [ABSTRACT FROM AUTHOR]

El artículo discurre sobre el proceso de visualizar datos y el desarrollo del periodismo digital. El autor comenta sobre el uso de Internet en la visualización de datos, incluyendo la proliferación de aplicaciones como iCharts, Google Charts y GetBulbs, las cuales ayudan a construir data visual.

The article offers information on the importance of genetic data visualization. It reports that the process of data visualization aimed at providing facility to users for exploring and explaining data by using interactive software which can be helpful in recognizing genetic patterns. It informs that the process helps the user to easily understanddata as it possesses a well-designed graphical depictions of information with simple perceptual inferences.