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1 – 10 of over 15000
Article
Publication date: 1 December 2006

Dumitru Radoiu, Calin Enachescu and Osei Adjei

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…

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Originality/value

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

Details

Engineering Computations, vol. 23 no. 8
Type: Research Article
ISSN: 0264-4401

Keywords

Article
Publication date: 6 December 2023

Mengxi Zhou, Selena Steinberg, Christina Stiso, Joshua A. Danish and Kalani Craig

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

Abstract

Purpose

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

Design/methodology/approach

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.

Findings

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.

Originality/value

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.

Details

Information and Learning Sciences, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2398-5348

Keywords

Book part
Publication date: 15 July 2019

David E. Caughlin and Talya N. Bauer

Data visualizations in some form or another have served as decision-support tools for many centuries. In conjunction with advancements in information technology, data

Abstract

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.

Details

Research in Personnel and Human Resources Management
Type: Book
ISBN: 978-1-78973-852-0

Keywords

Article
Publication date: 21 August 2017

Xiaoming Zhang, Huilin Chen, Yanqin Ruan, Dongyu Pan and Chongchong Zhao

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…

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Originality/value

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.

Details

International Journal of Web Information Systems, vol. 13 no. 3
Type: Research Article
ISSN: 1744-0084

Keywords

Article
Publication date: 26 January 2021

Adli Hamdam, Ruzita Jusoh, Yazkhiruni Yahya, Azlina Abdul Jalil and Nor Hafizah Zainal Abidin

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…

2192

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Research limitations/implications

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.

Originality/value

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.

Details

Accounting Research Journal, vol. 35 no. 1
Type: Research Article
ISSN: 1030-9616

Keywords

Article
Publication date: 4 March 2022

Carrie E. Finholm and Tamara L. Shreiner

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…

Abstract

Purpose

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.

Design/methodology/approach

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

Findings

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.

Practical implications

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.

Originality/value

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.

Details

Social Studies Research and Practice, vol. 17 no. 2
Type: Research Article
ISSN: 1933-5415

Keywords

Article
Publication date: 5 January 2024

Dennis Mathaisel

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…

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Research limitations/implications

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.

Practical implications

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.

Social implications

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

Originality/value

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.

Details

Journal of Information, Communication and Ethics in Society, vol. 22 no. 1
Type: Research Article
ISSN: 1477-996X

Keywords

Article
Publication date: 7 April 2015

Susan Gardner Archambault, Joanne Helouvry, Bonnie Strohl and Ginger Williams

– 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.

4171

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Originality/value

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.

Details

Library Hi Tech News, vol. 32 no. 2
Type: Research Article
ISSN: 0741-9058

Keywords

Article
Publication date: 23 March 2023

David Holdsworth and Adam Zagorecki

This study aims to examine the use of data visualization as a tool to support practitioner-led organizational learning within the emergency services. The authors investigate how…

143

Abstract

Purpose

This study aims to examine the use of data visualization as a tool to support practitioner-led organizational learning within the emergency services. The authors investigate how data visualization can support visual communication and the analysis of emergency response data to promote system improvement.

Design/methodology/approach

The authors investigate if communication data, presented as node-link diagrams, can be understood and evaluated by firefighters. Objective understanding of the communication network is measured quantitatively, while subject judgement of the emergency response system is measured qualitatively and compared to prior system evaluation outcomes. The authors compare different data visualization layouts and assess their value in supporting practitioner evaluation of emergency response systems.

Findings

The authors find that while firefighters are largely unfamiliar with their use, data visualizations function as a tool for visual communication and analysis. The authors identify the importance of visualization design and the difficulty in representing characteristics of a dynamic network within static diagrams. The authors also find some correlation between layout design and how respondents interpret visual data.

Originality/value

Results demonstrate the value of data visualization to support practitioner-led organizational learning and suggest future work to support the development of emergency response management.

Details

The Learning Organization, vol. 30 no. 2
Type: Research Article
ISSN: 0969-6474

Keywords

Article
Publication date: 13 August 2019

Chengyee Janie Chang and Yan Luo

This paper aims to examine major cognitive biases in auditors’ analyses involving visualization, as well as proposes practical approaches to address such biases in data

2140

Abstract

Purpose

This paper aims to examine major cognitive biases in auditors’ analyses involving visualization, as well as proposes practical approaches to address such biases in data visualization.

Design/methodology/approach

Using the professional judgment framework of KPMG (2011), this study performs an analysis of whether and how five major types of cognitive biases (framing, availability, overconfidence, anchoring and confirmation) may occur in an auditor’s data visualization and how such biases potentially compromise audit quality.

Findings

The analysis suggests that data visualization can trigger and/or aggravate the common cognitive biases in audit. If not properly addressed, such biases may adversely affect auditors' judgment and decision-making.

Practical implications

To ensure that data visualization improves audit efficiency and effectiveness, it is essential that auditors are aware of and successfully address cognitive biases in data visualization. Six practical approaches to debias cognitive biases in auditors’ visualization are proposed: using data visualization to complement rather than supplement traditional audit evidence; positioning data visualization to support rather than replace sophisticated analytics tools; using a dashboard with multiple dimensions; using both visualized and tabular data in analyses; assigning experienced audit staff; and providing pre-audit tutorials on cognitive bias and visualization.

Originality/value

The study raises awareness of psychological issues in an audit setting.

Details

Managerial Auditing Journal, vol. 36 no. 1
Type: Research Article
ISSN: 0268-6902

Keywords

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