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This paper aims to review and critically assess the role that data visualizations played as communication media tools to help society during a worldwide crisis. This paper re-creates and analyzes several visualizations, critically and ethically assesses their strengths and limitations and provides a set of best practices that are informative, accurate, ethical and engaging at each stage in a reader’s interest.

The paper bases its methodology on the construct of “The Network Society” (Van Dijk, 2006; Castells, 2000, 2006) by creating a series of social networked visualizations, identifying the challenges and pitfalls associated with this communication approach and suggesting best practices in information communication technology. The case study is COVID-19.

The research in this study found that visual data dashboards and interactive Web-based charts did play a significant role in helping society understand COVID-19’s impact to make better informed decisions about society’s health and safety.

Visual expositions of data do have strengths and weaknesses depending on how they are designed, how they communicate the story and how they are ethically deployed. Best practices are provided to help mitigate these limitations.

Visualizations are certainly not new, but the technology for rapidly developing and sharing them is new. Visual expositions provide an effective media for communicating complex information to a networked society.

Visual expositions provide an effective media for communicating complex information to a networked society.

This paper highlights the significance of the need to understand complex data in a crisis in a visual format and to communicate the information quickly, persuasively, effectively and ethically to a networked audience.

This study aims to explore how network visualization provides opportunities for learners to explore data literacy concepts using locally and personally relevant data.

The researchers designed six locally relevant network visualization activities to support students’ data reasoning practices toward understanding aggregate patterns in data. Cultural historical activity theory (Engeström, 1999) guides the analysis to identify how network visualization activities mediate students’ emerging understanding of aggregate data sets.

Pre/posttest findings indicate that this implementation positively impacted students’ understanding of network visualization concepts, as they were able to identify and interpret key relationships from novel networks. Interaction analysis (Jordan and Henderson, 1995) of video data revealed nuances of how activities mediated students’ improved ability to interpret network data. Some challenges noted in other studies, such as students’ tendency to focus on familiar concepts, are also noted as teachers supported conversations to help students move beyond them.

To the best of the authors’ knowledge, this is the first study the authors are aware of that supported elementary students in exploring data literacy through network visualization. The authors discuss how network visualizations and locally/personally meaningful data provide opportunities for learning data literacy concepts across the curriculum.

This chapter explores the development of social science visualizations as cultural objects within art worlds. The research examines artworks as social science visualizations to show the importance of conducting analysis within distinctive social, institutional, and cultural environments. To make these arguments, the chapter outlines some of the key features of art worlds as they have been analyzed by cultural sociologists and anthropologists. We point out how cultures of reception and institutional intermediaries, such as museums, have historically shaped the construction of artworks, which are never produced or interpreted in a vacuum. The chapter closes with a call to expand both the application of social science visualizations and our understanding of such visualizations as subject to similar art world dynamics. Such visualizations, it is argued, constitute key components of social research practice increasingly oriented toward a digitally connected public hungry for visual interpretations of contemporary social developments.

The purpose of this paper is to present the investigation on contemporary applications of game design in architectural visualization, urban environmental planning and the results to address the problems of traditional methods specifically in terms of interactivity and visualization. The authors present the prototype that incorporates information modeling and virtual reality (VR) into interactive architectural visualization.

The proposed system supports a virtual walkthrough process that allows users to navigate in an architectural space of their imagination and design. The immersion in the design of living space or environment has been made possible through the inclusion of VR through the use of WebVR technology to deploy the design to be experienced.

This study investigates and establishes a framework that explores the intricacies of 3 imensional (3D) Architectural Visualization in a real-time engine by designing a visual experience with a better level of user interaction and then deploying it through VR.

To the best of the authors’ knowledge, this is one of the few experimental frameworks which perfectly integrates VR for visualization in digital home design environments. The prospective applications of this framework are in several fields of construction innovation, architectural design, 3D modeling, virtual and augmented reality.

This study investigates whether the visualization of agricultural products influences consumers’ purchase intentions in the context of farmer-assisted livestreaming in China. Moreover, it explores the moderating effect of packaging functionality and the mediating effect of consumer trust.

Consumers in China from multiple social media platforms participated in this survey, which yielded 333 valid responses for analysis.

The results revealed a positive relationship between the video presentation about the agricultural production process and consumers’ purchase intention, which is mediated by consumers’ trust. Meanwhile, packaging functionality moderates the relationship between agricultural product visualization and consumers’ purchase intentions as well as the indirect effect of consumers’ trust.

This study extends the application of the stimulus-organism-response (SOR) model to the field of farmer-assisted livestreaming. By building a more detailed model, this study adds to knowledge on the influencing mechanisms of consumers’ purchase intentions in farmer-assisted livestreaming.

This study was carried out to examine the volume and annual growth pattern of research on e-health literacy research, investigate the open-access types of e-health literacy research and perform document production by country and by sources. The study also mapped the keywords used by authors to represent e-health literacy research and performed an analysis of the clusters of the keywords to reveal the thematic focus of research in the area.

The research was guided by a bibliometric approach involving visualization using VosViewer. Data were sourced from Scopus database using a syntax that was tested and verified to be capable of yielding reliable data on the subject matter. The analysis in this study was based on bibliographic data and keywords.

A total number of 1,176 documents were produced during 2006 and 2022. The majority of the documents (18.90%) were published based on hybrid open-access processes, and the USA has the highest contributions. The Journal of Medical Internet Research is the venue for most of the documents on the subject. The 1,176 documents were described by 5,047 keywords, 4.29 keywords per document, and the keywords were classified into five clusters that aptly capture the thematic structure of research in the area.

e-Health literacy has experienced significant growth in research production from 2006 to 2022, with an average of 69 documents per year. Research on e-health literacy initially had low output but began to increase in 2018. The majority of e-health literacy documents are available through open access, with the USA being the leading contributor. The analysis of keywords reveals the multifaceted nature of e-health literacy, including access to information, attitudes, measurement tools, awareness, age factors and communication. Clusters of keywords highlight different aspects of e-health literacy research, such as accessibility, attitudes, awareness, measurement tools and the importance of age, cancer, caregivers and effective communication in healthcare.

This study has practical implications for health promotion. There is also the element of patient empowerment in which case patients are allowed to take an active role in their healthcare. By understanding their health information and having access to resources that help them manage their conditions, patients can make informed decisions about their healthcare. Finally, there is the issue of improved health outcomes which can be achieved by improving patients' e-health literacy. Visualisation of e-health literacy can help bridge the gap between patients and healthcare providers, promote patient-centered care and improve health outcomes.

Research production on e-Health literacy has experienced significant growth from 2006 to 2022, with an average of 69 documents per year. Many e-health literacy documents are available through open access, and the USA is the leading contributor. The analysis of keywords reveals the nature of e-health literacy, including access to information, attitudes, measurement tools, awareness and communication. The clusters of keywords highlight different aspects of e-health literacy research, such as accessibility, attitudes, awareness, measurement tools and the importance of age, cancer, caregivers, and effective communication in healthcare.

This compact case provides a relatively large data set that students explore using visualization and a Tableau dynamic dashboard that they create. Students were asked to describe what the data set contained in relation to employee attrition experience of Baca Beverage Distributors (BBD). The application and managerial questions are set in human resources and a company that is facing high attrition during the pandemic.

BBD shared their data and problem scenario for this compact case. The protagonist, Morgan Matthews, was the authors’ contact and provided significant clarification and guidance about the data. Both the company and the protagonist have been disguised. Some of the job positions have been rephrased. All names of employees, supervisors and managers have been replaced with codes.

During the 2020–2022 pandemic years, BBD experienced, like many companies, a higher than usual employee turnover rate and Morgan Matthews, Director of People, was concerned. Not only was it time-consuming, expensive and disruptive but the company had prided itself on being a good place to work. Were they hiring the right people, people that fit the company culture and people that fit the positions for which they were hired? The company had been using the Predictive Index [1] when on-boarding employees. In addition, there were results from self-reviews and manager reviews that could be used. Morgan wondered if data visualization and visual analytics would be useful in describing their employees and whether it would reveal any opportunities to improve the turnover rate. Before seeking a solution for the high turnover, it was important to step back and learn what the data said about who was leaving and the reasons they gave for leaving.

This compact case can be used in courses that include visualization using Tableau and dashboards. As it is a compact case, it requires less preparation time from the students and less class time for discussion. The case is for students who have been recently introduced to business analytics, specifically visualization and data storytelling with Tableau. For this reason, significant guidance has been provided in the case assignment. The level of the case can be adjusted by the amount of guidance provided in the case assignment. Courses include introduction to business analytics, descriptive analytics and visualization, communication through data storytelling. The case can be used for all modalities – in person, hybrid, online. The authors use it here for visualization and dynamic dashboards but using the same data set and compact case description, exploratory data analysis could be assigned.

Supplementary material for this article can be found online.

The current study aims to map the scientific output of grey literature (GL) through bibliometric approaches.

The source for data extraction is a comprehensive “indexing and abstracting” database, “Web of Science” (WOS). A lexical title search was applied to get the corpus of the study – a total of 4,599 articles were extracted for data analysis and visualisation. Further, the data were analysed by using the data analytical tools, R-studio and VOSViewer.

The findings showed that the “publications” have substantially grown up during the timeline. The most productive phase (2018–2021) resulted in 47% of articles. The prominent sources were PLOS One and NeuroImage. The highest number of papers were contributed by Haddaway and Kumar. The most relevant countries were the USA and UK.

The study is useful for researchers interested in the GL research domain. The study helps to understand the evolution of the GL to provide research support further in this area.

The present study provides a new orientation to the scholarly output of the GL. The study is rigorous and all-inclusive based on analytical operations like the research networks, collaboration and visualisation. To the best of the authors' knowledge, this manuscript is original, and no similar works have been found with the research objectives included here.

Artificial Intelligence (AI) is an emerging technology and turned into a field of knowledge that has been consistently displacing technologies for a change in human life. It is applied in all spheres of life as reflected in the review of the literature section here. As applicable in the field of libraries too, this study scientifically mapped the papers on AAIL and analyze its growth, collaboration network, trending topics, or research hot spots to highlight the challenges and opportunities in adopting AI-based advancements in library systems and processes.

The study was developed with a bibliometric approach, considering a decade, 2012 to 2021 for data extraction from a premier database, Scopus. The steps followed are (1) identification, selection of keywords, and forming the search strategy with the approval of a panel of computer scientists and librarians and (2) design and development of a perfect algorithm to verify these selected keywords in title-abstract-keywords of Scopus (3) Performing data processing in some state-of-the-art bibliometric visualization tools, Biblioshiny R and VOSviewer (4) discussing the findings for practical implications of the study and limitations.

As evident from several papers, not much research has been conducted on AI applications in libraries in comparison to topics like AI applications in cancer, health, medicine, education, and agriculture. As per the Price law, the growth pattern is exponential. The total number of papers relevant to the subject is 1462 (single and multi-authored) contributed by 5400 authors with 0.271 documents per author and around 4 authors per document. Papers occurred mostly in open-access journals. The productive journal is the Journal of Chemical Information and Modelling (NP = 63) while the highly consistent and impactful is the Journal of Machine Learning Research (z-index=63.58 and CPP = 56.17). In the case of authors, J Chen (z-index=28.86 and CPP = 43.75) is the most consistent and impactful author. At the country level, the USA has recorded the highest number of papers positioned at the center of the co-authorship network but at the institutional level, China takes the 1st position. The trending topics of research are machine learning, large dataset, deep learning, high-level languages, etc. The present information system has a high potential to improve if integrated with AI technologies.

The number of scientific papers has increased over time. The evolution of themes like machine learning implicates AI as a broad field of knowledge that converges with other disciplines. The themes like large datasets imply that AI may be applied to analyze and interpret these data and support decision-making in public sector enterprises. Theme named high-level language emerged as a research hotspot which indicated that extensive research has been going on in this area to improve computer systems for facilitating the processing of data with high momentum. These implications are of high strategic worth for policymakers, library stakeholders, researchers and the government as a whole for decision-making.

The analysis of collaboration, prolific authors/journals using consistency factor and CPP, testing the relationship between consistency (z-index) and impact (h-index), using state-of-the-art network visualization and cluster analysis techniques make this study novel and differentiates it from the traditional bibliometric analysis. To the best of the author's knowledge, this work is the first attempt to comprehend the research streams and provide a holistic view of research on the application of AI in libraries. The insights obtained from this analysis are instrumental for both academics and practitioners.

Mucormycosis has evolved as a post-COVID-19 complication globally, especially in India. The research on fungus has been very primitive, and many scientific publications have been discovered. The current COVID-19 pandemic needs further investigation into this unusual fungal infection. This review study aims to provide a pen-picture to researchers, science policymakers and scientists about different bibliometric indicators related to the research literature on mucormycosis.

The quantitative research was conducted using the established procedure of bibliometric investigation on data collected from Scopus from 2011 to 2020 using a validated search query. The search query consisted of keywords “Mucormycosis” or “Mucormycoses” or “Mucormycose” or “Mucorales Infection” or “Mucorales Infections” or “Black Fungus Infection” or “Black Fungus Infections” or “Zygomycosis” in the “Title-Keyword-Abstract” search option for data extraction. The analysis of data is performed using MS-Excel. Mapping was done with state-of-the-art visualization tools Biblioshiny and VOSviewer, using bibliometric indicators as units of analysis.

The analysis reveals that the first publication on this topic was reported from 1923 onwards. In total, 9,423 authors contributed 1,896 papers with 11,437 collaborated authors, documents per author are 0.201, authors per document are 4.97 and co-authors per document are 6.03. Total records were published in 779 journals in the English language from 75 countries globally. Mucormycosis literature is mostly open access, with 1,210 publications available via different open access routes. The highest number of articles (204) published in the journal “Mycoses” with 1,333 authors received 4,875 cited references, and the h-index has 24. The growth of publications is exponential, as depicted by the Price Law. The USA has recorded a maximum number of publications at both country and institutional levels compared to the other nations. There has been extensive research on mucormycosis before the outbreak as a post-COVID complication, as indicated by the highest number of publications in 2019.

The research hot spots have altered from “Mucormycosis,” “fungi,” “Zygomycosis” and “Drug efficacy”, “Drug Safety” to “Microbiology,” “Pathology,” “nucleotide sequence,” “surgical debridement” which indicates that potential area of research in the near future will be concerned with more extensive research in mucormycosis to develop standard treatment procedures to fight this infection. The quantity of scientific publications has also increased over time. The research and health community are called upon to join forces to activate existing knowledge, generate new insights and develop decision-supporting tools for health authorities in different nations to leverage vaccination in its transformational role toward successfully attaining nil cases of COVID-19.

The analysis of collaboration, findings, the research networks and visualization makes this study novel and separates from traditional metrics analysis. To the best of the authors’ knowledge, this work is original, and no similar studies have been found with the objectives included here.