This study considered the interplay of simple versus perspective graphical information on aesthetic preference, instructional effectiveness, and retention. Students in an introductory U.S. government course were prese...
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This study considered the interplay of simple versus perspective graphical information on aesthetic preference, instructional effectiveness, and retention. Students in an introductory U.S. government course were presented with examples of 2-D and 3-D graphs and asked to choose which was pleasing to the eye and which was most useful in answering questions about the graph's content. The results of this study indicated that when visual appeal was the only criterion, subject choices overall were approximately evenly matched. When subjects were required to extract information from graphs, they used simple graphs almost 3 times more often than elaborate graphs. information drawn from bar and circle graphs was extracted more accurately than the other three types of graphs.
Aim/Purpose This journal paper seeks to understand historical aspects of data management, leading to the current data issues faced by organizational executives in relation to big data and how best to present the infor...
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Aim/Purpose This journal paper seeks to understand historical aspects of data management, leading to the current data issues faced by organizational executives in relation to big data and how best to present the information to circumvent big data challenges for executive strategic decision making. Background This journal paper seeks to understand what executives value in data visualiza-tion, based on the literature published from prior data studies. Methodology The qualitative methodology was used to understand the sentiments of execu-tives and data analysts using semi-structured interview techniques. Contribution The preliminary findings can provide practical knowledge for data visualization designers, but can also provide academics with knowledge to reflect on and use, specifically in relation to information systems (IS) that integrate human experi-ence with technology in more valuable and productive ways. Findings Preliminary results from interviews with executives and data analysts point to the relevance of understanding and effectively presenting the data source and the data journey, using the right data visualization technology to fit the nature of the data, creating an intuitive platform which enables collaboration and new-ness, the data presenter's ability to convey the data message and the alignment of the visualization to core the objectives as key criteria to be applied for suc-cessful data visualizations Recommendations for Practitioners Practitioners, specifically data analysts, should consider the results highlighted in the findings and adopt such recommendations when presenting data visualiza-tions. These include data and premise understanding, ensuring alignment to the executive's objective, possessing the ability to convey messages succinctly and clearly to the audience, having knowledge of the domain to answer questions effectively, and using the right technology to convey the message. Recommendation for Researchers The importance of human cognitiv
Background: The development of Clinical data Warehouses (CDWs) has greatly increased access to big data in medical research. However, the lack of standardization among different data models hampers interoperability an...
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Background: The development of Clinical data Warehouses (CDWs) has greatly increased access to big data in medical research. However, the lack of standardization among different data models hampers interoperability and, consequently, the research potential of these vast data resources. Moreover, data manipulation and analysis require advanced programming skills, a skill set that healthcare professionals often lack. Methods: To address these issues, we created an open source, low-code and collaborative data science platform for manipulating, visualizing and analyzing healthcare data using graphical tools alongside an advanced programming interface. The software is based on the OMOP Common data Model. Results: LinkR enables users to generate studies using data imported from multiple sources. The software organizes the studies into two main sections: individual and population data sections. In the individual data section, user-friendly graphical tools allow users to customize data presentation, recreating the equivalent of a medical record, according to the needs of their study. The population data section is designed for conducting statistical analyses through both graphical and programming interfaces. The application also integrates a Git module, streamlining collaboration and facilitating shared data analysis across research centers. The platform was tested with datasets including the OMOP database (46,520 patients and over 36 million rows in the measurement table) during the InterHop datathon with 12 concurrent users. Usability testing yielded a median System Usability Scale (SUS) score of 75 [63.8-85.6], indicating high user satisfaction. Conclusion: LinkR is a low-code data science platform that democratizes access, manipulation, and analysis of data from clinical data warehouses and facilitates collaborative work on healthcare data, using an open science approach.
Current education systems use data visualization to present the data in a more comprehensible format. Augmented data visualization is an extended version to present the data in a 2D or 3D form in our field of vision. ...
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ISBN:
(纸本)9781665494755
Current education systems use data visualization to present the data in a more comprehensible format. Augmented data visualization is an extended version to present the data in a 2D or 3D form in our field of vision. This study conducted a systematic literature review to identify the current state of the art research in augmented reality and potential future research. Research paid especial attention towards the effective use of augmented reality for data visualization to offer a better pedagogical experience. A total of 39 studies have been filtered between 2017 to 2021 from two recognized databases, IEEE Xplore and ScienceDirect. Three research questions are designed for further analysis. Finally, the paper concludes with a future projection and uncovers research gaps that need to be addressed.
In self-tracking applications, data visualizations play a fundamental role in delivering efficient information and creating personalized user experiences. Literature consistently indicates that data visualization is a...
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ISBN:
(纸本)9781450392464
In self-tracking applications, data visualizations play a fundamental role in delivering efficient information and creating personalized user experiences. Literature consistently indicates that data visualization is a powerful tool to make data persuasive and improve motivation. However, how to leverage different data visualizations to boost motivation remains largely unknown. In this study, the researcher explores the effects of different data visualizations on user motivation within self-tracking mobile applications. Through design space analysis and semi-structured interviews, the researcher defines a set of design factors that impact users' exercise motivation at different levels of exercise adoption. Based on these factors, the researcher delivers a set of practical design suggestions for design practitioners and people who create visualizations for large data sets.
Network attacks have become the fundamental threat to today's largely interconnected computer system. Intrusion detection system (IDS) is indispensable to defend the system in the face of increasing vulnerabilitie...
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Network attacks have become the fundamental threat to today's largely interconnected computer system. Intrusion detection system (IDS) is indispensable to defend the system in the face of increasing vulnerabilities. While a number of information visualization software frameworks exist, creating new visualizations, especially those that involve novel visualization metaphors, interaction techniques, data analysis strategies, and specialized rendering algorithms, is still often a difficult process. To facilitate the creation of novel visualizations this paper presents a new framework that is designed with using data visualization technique for analysis and visualizes snort result data for user. The framework suggests PHP and CSS as data visualization technique and snort as intrusion detection system (IDS).
With the advent of the data era, and of new, more intelligent interfaces for supporting decision making, there is a growing need to define, model and assess human ability and data visualizations usability for a better...
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The objective of this study is to present and discuss how data visualization can be incorporated into teaching approaches by business faculty in introductory business statistics to strengthen business students' pr...
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The objective of this study is to present and discuss how data visualization can be incorporated into teaching approaches by business faculty in introductory business statistics to strengthen business students' practical skills. data visualization lessens difficulties in learning statistics by providing opportunities to illustrate analytical findings in graphic form, which is essential for learners with different learning styles. Familiarizing students with Excel, Python, or other software in introductory business statistics is beneficial in helping them attain statistical literacy by analyzing real-world data such as COVID-19 statistics. Using such data equips students with knowledge of statistical implementation-a core skill in the business world.
In order to meet the requirements of high-dimensional data processing in the information field, this paper aims to explore methods and techniques for visualizing general data resource clustering data. Through the visu...
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In order to meet the requirements of high-dimensional data processing in the information field, this paper aims to explore methods and techniques for visualizing general data resource clustering data. Through the visual mapping of dimensionality reduction and high-dimensional data, a visual learning model for visual influencing factors is established. The visual system model approach was tested using the IRIS dataset from the University of California Irvine database (UCL) database. The results show that the model can effectively analyze the data set, visualize the characteristics of IRIS data in real time, achieve the expected results, and point the way for other data visualization models.
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