Matching Items (4)
Filtering by
- All Subjects: Data Visualization
- Creators: D'Angelo, Barbara J.
Description
In visualizing information hierarchies, icicle plots are efficient diagrams in that they provide the user a straightforward layout for different levels of data in a hierarchy and enable the user to compare items based on the item width. However, as the size of the hierarchy grows large, the items in an icicle plot end up being small and indistinguishable. In this thesis, by maintaining the positive characteristics of traditional
icicle plots and incorporating new features such as dynamic diagram and active layer, we developed an interactive visualization that allows the user to selectively drill down or roll up to review different levels of data in a large hierarchy, to change the hierarchical
structure to detect potential patterns, and to maintain an overall understanding of the
current hierarchical structure.
icicle plots and incorporating new features such as dynamic diagram and active layer, we developed an interactive visualization that allows the user to selectively drill down or roll up to review different levels of data in a large hierarchy, to change the hierarchical
structure to detect potential patterns, and to maintain an overall understanding of the
current hierarchical structure.
ContributorsWu, Bi (Author) / Maciejewski, Ross (Thesis advisor) / Runger, George C. (Committee member) / Davulcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2014
Description
This paper presents the results of an empirical analysis of deceptive data visualizations paired with explanatory text. Data visualizations are used to communicate information about important social issues to large audiences and are found in the news, social media, and the Internet (Kirk, 2012). Modern technology and software allow people and organizations to easily produce and publish data visualizations, contributing to data visualizations becoming more prevalent as a means of communicating important information (Sue & Griffin, 2016). Ethical transgressions in data visualizations are the intentional or unintentional use of deceptive techniques with the potential of altering the audience’s understanding of the information being presented (Pandey et al., 2015). While many have discussed the importance of ethics in data visualization, scientists have only recently started to look at how deceptive data visualizations affect the reader. This study was administered as an on-line user survey and was designed to test the deceptive potential of data visualizations when they are accompanied by a paragraph of text. The study consisted of a demographic questionnaire, chart familiarity assessment, and data visualization survey. A total of 256 participants completed the survey and were evenly distributed between a control (non-deceptive) survey or a test (deceptive) survey in which participant were asked to observe a paragraph of text and data visualization paired together. Participants then answered a question relevant to the observed information to measure how they perceived the information to be. The individual differences between demographic groups and their responses were analyzed to understand how these groups reacted to deceptive data visualizations compared to the control group. The results of the study confirmed that deceptive techniques in data visualizations caused participants to misinterpret the information in the deceptive data visualizations even when they were accompanied by a paragraph of explanatory text. Furthermore, certain demographics and comfort levels with chart types were more susceptible to certain types of deceptive techniques. These results highlight the importance of education and practice in the area of data visualizations to ensure deceptive practices are not utilized and to avoid potential misinformation, especially when information can be called into question.
ContributorsO'Brien, Shaun (Author) / Laure, Claire (Thesis advisor) / Brumberger, Eva (Committee member) / D'Angelo, Barbara J. (Committee member) / Arizona State University (Publisher)
Created2017
Description
The Global Change Assessment Model (GCAM) is an integrated assessment tool for exploring consequences and responses to global change. However, the current iteration of GCAM relies on NetCDF file outputs which need to be exported for visualization and analysis purposes. Such a requirement limits the uptake of this modeling platform for analysts that may wish to explore future scenarios. This work has focused on a web-based geovisual analytics interface for GCAM. Challenges of this work include enabling both domain expert and model experts to be able to functionally explore the model. Furthermore, scenario analysis has been widely applied in climate science to understand the impact of climate change on the future human environment. The inter-comparison of scenario analysis remains a big challenge in both the climate science and visualization communities. In a close collaboration with the Global Change Assessment Model team, I developed the first visual analytics interface for GCAM with a series of interactive functions to help users understand the simulated impact of climate change on sectors of the global economy, and at the same time allow them to explore inter comparison of scenario analysis with GCAM models. This tool implements a hierarchical clustering approach to allow inter-comparison and similarity analysis among multiple scenarios over space, time, and multiple attributes through a set of coordinated multiple views. After working with this tool, the scientists from the GCAM team agree that the geovisual analytics tool can facilitate scenario exploration and enable scientific insight gaining process into scenario comparison. To demonstrate my work, I present two case studies, one of them explores the potential impact that the China south-north water transportation project in the Yangtze River basin will have on projected water demands. The other case study using GCAM models demonstrates how the impact of spatial variations and scales on similarity analysis of climate scenarios varies at world, continental, and country scales.
ContributorsChang, Zheng (Author) / Maciejewski, Ross (Thesis advisor) / Sarjoughian, Hessam S. (Committee member) / White, Dave (Committee member) / Luo, Wei (Committee member) / Arizona State University (Publisher)
Created2015
Description
Grubhub's user reviews from the Apple IOS store were analyzed to provide alternate user experience (UX) solutions through answering the following:
1. How is Grubhub's mobile app meeting user expectations?
2. How can Grubhub improve the mobile app experience?
ContributorsDiaz, Samantha (Author) / Harris, LaVerne Abe (Degree committee member) / D'Angelo, Barbara J. (Degree committee member) / Mara, Andrew (Degree committee member)
Created2019-12-13