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Recent technological advances have created volumes of data such that, unless some effective methods are used to analyse them, they will be either wasted or under‐examined for their useful information content. Scientific data visualization is an attempt to use graphical and numerical tools to extract information contained in data and hence to allow its analysis. This paper seeks to present a systematic approach to the development of tools for scientific data visualization.

It is shown that the approach to implement these tools involves four major steps: description of a reference model, validation of the data process, description of the software component and the design and implementation of the visualization tool.

This approach is substantiated by defining conditions suitable for scientific data visualization processes, in a relaxed manner. These conditions are subsequently refined more formally. Definitions and theorems of the proofs are succinctly discussed.

The mathematical description of the visualization process is necessary to understand and maintain some significant reduction in errors in scientific visualization processes.

Responding to calls for accountants to engage with modern technologies and explore data visualisation within a three-dimensional (3D) environment, this study aims to explore whether social and environmental accounting (SEA) data visualisation is a promising use case for 3D game engine technology.

Drawing on visual perception and embodiment theories, this study uses photo-elicitation, a qualitative research method, to explore the usefulness of two-dimensional (2D) and 3D visualisations of sustainability information in a 3D virtual environment. This study provides three stimuli: numerical data, 2D visualisations and 3D visualisations, and asks open-ended questions regarding future applications. Twelve semi-structured interviews were conducted with academics, preparers and users of sustainability reports to obtain responses to these stimuli.

The key finding is that visualisation of SEA information may indeed be a strong use case for 3D game technology, but only for certain data and for certain audiences. Presenting information within a 3D virtual environment offered enhanced engagement and contextual understanding but reduced navigation speed and data clarity. Participants were enthusiastic about the potential of a museum-like experience, incorporating interactivity and community, but felt that the appropriate audience was more likely to be novices than experts.

This study suggests that deploying 3D game engine technology can be a powerful tool for presenting sustainability information but requires significant resources. The optimum audience is likely to be novices, and a key design principle is to ensure the virtual environment supports, rather than overwhelms, the information presented within that environment.

This study introduces a novel application of 3D visualisation technology within the SEA context, offering original insights into its potential to enhance user understanding and decision-making capabilities. This study highlights the technology’s value not as a replacement for traditional reporting but as a supplementary educational tool. The study also provides a novel setting for the photo-elicitation method, demonstrating this approach’s utility in a 3D environment.

This paper aims to demonstrate how the design of data visualisations can act as a tool to support social marketing messages in prompting behaviour change to reduce food waste using the Elaboration Likelihood Model (ELM) as a theoretical framework. It also responds to a lack of consumer-led insight to develop campaigns in reducing food waste.

The research uses data collected by the End Food Waste Cooperative Research Centre (EFW CRC) in Australia to determine which text-based campaign messages are most likely to prompt people toward reducing food waste. Behaviour change messages were first identified through workshops with 11 food waste experts, then explored through online focus group discussions with 18 participants from three food-wasting market segments. The messages were further tested via a quantitative survey among 1,000 decision makers in Australian households in their own homes, with the top three performing messages examined using summative content analysis.

The significant findings were that participants want to see 1) evidence of how adopting new behaviours would lead to financial savings and benefit the environment, and 2) concrete steps to reduce food waste. When examined through the ELM, the findings suggest that tools that encourage both cognitive and peripheral processing as a means of persuasion, like data visualisations, may be useful for changing food-wasting behaviours.

Applying principles from the field of communication design to the ELM has uncovered the potential for a cross-disciplinary approach to enhance theoretical frameworks for understanding consumer engagement with messages. This process in turn, may lead to the development of more effective behaviour change marketing strategies.

Six principles for using data visualisations in a social marketing campaign are proposed: personal relevance, ease of use, emotional storytelling, context, prioritising the message itself and long-term usage.

This study proposes that data visualisations could enhance the effectiveness of social marketing campaigns by leveraging consumer-derived insights and the persuasive capacity inherent in their theoretical underpinnings.

Data visualizations in some form or another have served as decision-support tools for many centuries. In conjunction with advancements in information technology, data visualizations have become more accessible and more efficient to generate. In fact, virtually all enterprise resource planning and human resource (HR) information system vendors offer off-the-shelf data visualizations as part of decision-support dashboards as well as stand-alone images and displays for reporting. Plus, advances in programing languages and software such as Tableau, Microsoft Power BI, R, and Python have expanded the possibilities of fully customized graphics. Despite the proliferation of data visualization, relatively little is known about how to design data visualizations for displaying different types of HR data to different user groups, for different purposes, and with the overarching goal of improving the ways in which users comprehend and interpret data visualizations for decision-making purposes. To understand the state of science and practice as they relate to HR data visualizations and data visualizations in general, we review the literature on data visualizations across disciplines and offer an organizing framework that emphasizes the roles data visualization characteristics (e.g., display type, features), user characteristics (e.g., experience, individual differences), tasks, and objectives (e.g., compare values) play in user comprehension, interpretation, and decision-making. Finally, we close by proposing future directions for science and practice.

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.

With the rapid development of materials informatics and the Semantic Web, the semantic-driven solution has emerged to improve traditional query technology, which is hard to discover implicit knowledge from materials data. However, it is a nontrivial thing for materials scientists to construct a semantic query, and the query results are usually presented in RDF/XML format which is not convenient for users to understand. This paper aims to propose an approach to construct semantic query and visualize the query results for metallic materials domain.

The authors design a query builder to generate SPARQL query statements automatically based on domain ontology and query conditions inputted by users. Moreover, a semantic visualization model is defined based on the materials science tetrahedron to support the visualization of query results in an intuitive, dynamic and interactive way.

Based on the Semantic Web technology, the authors design an automatic semantic query builder to help domain experts write the normative semantic query statements quickly and simply, as well as a prototype (named MatViz) is developed to visually show query results, which could help experts discover implicit knowledge from materials data. Moreover, the experiments demonstrate that the proposed system in this paper can rapidly and effectively return visualized query results over the metallic materials data set.

This paper mainly discusses an approach to support semantic query and visualization of metallic materials data. The implementation of MatViz will be a meaningful work for the research of metal materials data integration.

The role of big data and data analytics in the audit engagement process is evident. Notwithstanding, understanding how big data influences cognitive processes and, consequently, on the auditors’ judgment decision-making process is limited. The purpose of this paper is to present a conceptual framework on the cognitive process that may influence auditors’ judgment decision-making in the big data environment. The proposed framework predicts the relationships among data visualization integration, data processing modes, task complexity and auditors’ judgment decision-making.

The methodology to accomplish the conceptual framework is based on a thorough literature review that consists of theoretical discussions and comparative studies of other authors’ works and thinking. It also involves summarizing and interpreting previous contributions subjectively and narratively and extending the work in some fashion. Based on this approach, this paper formulates four propositions about data visualization integration, data processing modes, task complexity and auditors’ judgment decision-making. The proposed framework was built from cognitive theory addressing how auditors process data into useful information to make judgment decision-making.

The proposed framework expects that the cognitive process of data visualization integration and intuitive data processing mode will improve auditors’ judgment decision-making. This paper also contends that task complexity may influence the cognitive process of data visualization integration and processing modes because of the voluminous nature of data and the complexity of business processes. Hence, it is also expected that the relationships between data visualization integration and audit judgment decision-making and between processing mode and audit judgment decision-making will be moderated by task complexity.

There is a dearth of studies examining how big data and big data analytics affect auditors’ cognitive processes in making decisions. This paper will help researchers and auditors understand the behavioral consequences of data visualization integration and data processing mode in making judgment decision-making, given a certain level of task complexity.

With the advent of big data and the evolution of innovative audit procedures, the constructed framework can be used as a theoretical foundation for future empirical studies concerning auditors’ judgment decision-making. It highlights the potential of big data to transform the nature and practice of accounting and auditing.

Over the last several decades, individuals have had access to and encountered more data than ever before. Data can be used to persuade people how to vote, support policies, adopt arguments or agendas and buy products. Data directly relate to our everyday lives including our finances, careers, educational performance and health. Therefore, it is more critical than ever for individuals and students to become data literate. This article presents a study examining the use of data visualizations in K-12 history lessons from eight popular online curricular resources.

The method employed was content analysis of 1,356 lesson plans across the eight websites.

About a third of the history lessons reviewed contained data visualizations, but there were mixed results across websites as to whether lesson plans provided guidance on data literacy instruction.

Because online lesson plans frequently miss opportunities to use data visualizations to deepen students’ understanding and support data literacy skills, teachers need to be aware of missed opportunities and consider ways to enhance or revise the lessons.

This study provides insight into the likelihood that history lessons found on popular online curriculum websites will support data literacy instruction. The lack of pedagogical guidance in such curricular resources underscores the importance of including data literacy in teacher education and professional development.

This paper aims to provide a framework for thinking about meaningful data visualization in ways that can be applied to routine statistics collected by libraries.

An overview of common data display methods is provided, with an emphasis on tables, scatter plots, line charts, bar charts, histograms, pie charts and infographics. Research on “best practices” in data visualization design is presented; also provided is a comparison of free online data visualization tools.

Different data display methods are best suited for different quantitative relationships. There are rules to follow for optimal data visualization design. Ten free online data visualization tools are recommended by the authors.

Evidence-based libraries collect and use data to affect change and to support departmental and institutional accreditation standards. Proper data visualization allows libraries to communicate their message in a more compelling and interesting way, while assisting in the understanding of complex data.

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.