Kaleidographic

2019 ◽  
Vol 24 (2) ◽  
pp. 245-261
Author(s):  
Helen Caple ◽  
Laurence Anthony ◽  
Monika Bednarek
Keyword(s):  
Case Studies ◽  
Data Visualization ◽  
Corpus Linguistics ◽  
Visualization Tool ◽  
Multimodal Discourse ◽  
Corpus Studies ◽  
Interactive Data

Abstract Kaleidographic is a dynamic and interactive data visualization tool that allows users to observe and explore relations between any number of variables. The tool is useful for displaying the complex ways in which textual elements interact across a range of texts. Thus far, the tool has been used to display the results of corpus studies as well as corpus-assisted multimodal discourse analyses that investigate text-image relations. To facilitate broader applications of the tool, it is now publicly available online for use without charge. This paper explains the background and motivation for Kaleidographic and presents two case studies demonstrating its utility. Limitations of the tool are discussed and its potential uses in corpus linguistics research and beyond are introduced.

scholarly journals An Interactive Data Visualization Framework for Exploring Geospatial Environmental Datasets and Model Predictions

Water ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2928
Author(s):  
Jeffrey D. Walker ◽  
Benjamin H. Letcher ◽  
Kirk D. Rodgers ◽  
Clint C. Muhlfeld ◽  
Vincent S. D’Angelo
Keyword(s):  
Decision Making ◽  
Case Studies ◽  
Data Visualization ◽  
Large Scale ◽  
Research Management ◽  
Web Based ◽  
Environmental Models ◽  
Potential Benefits ◽  
Interactive Data ◽  
Data Visualizations

With the rise of large-scale environmental models comes new challenges for how we best utilize this information in research, management and decision making. Interactive data visualizations can make large and complex datasets easier to access and explore, which can lead to knowledge discovery, hypothesis formation and improved understanding. Here, we present a web-based interactive data visualization framework, the Interactive Catchment Explorer (ICE), for exploring environmental datasets and model outputs. Using a client-based architecture, the ICE framework provides a highly interactive user experience for discovering spatial patterns, evaluating relationships between variables and identifying specific locations using multivariate criteria. Through a series of case studies, we demonstrate the application of the ICE framework to datasets and models associated with three separate research projects covering different regions in North America. From these case studies, we provide specific examples of the broader impacts that tools like these can have, including fostering discussion and collaboration among stakeholders and playing a central role in the iterative process of data collection, analysis and decision making. Overall, the ICE framework demonstrates the potential benefits and impacts of using web-based interactive data visualization tools to place environmental datasets and model outputs directly into the hands of stakeholders, managers, decision makers and other researchers.

Interactive Data Visualization Techniques Applied to Healthcare Decision Making

2017 ◽  
pp. 1157-1171 ◽  
Author(s):  
Zhecheng Zhu ◽  
Heng Bee Hoon ◽  
Kiok-Liang Teow
Keyword(s):  
Decision Making ◽  
Case Studies ◽  
Data Visualization ◽  
Capacity Planning ◽  
Healthcare Systems ◽  
Healthcare Decision ◽  
Healthcare Decision Making ◽  
Patient Profiling ◽  
Interactive Data ◽  
Visualization Techniques

Data visualization techniques are widely applied in all kinds of organizations, turning tables of numbers into visualizations for discovery, information communication, and knowledge sharing. Data visualization solutions can be found everywhere in healthcare systems from hospital operations monitoring and patient profiling to demand projection and capacity planning. In this chapter, interactive data visualization techniques are discussed and their applications to various aspects of healthcare systems are explored. Compared to static data visualization techniques, interactive ones allow users to explore the data and find the insights themselves. Four case studies are given to illustrate how interactive data visualization techniques are applied in healthcare: summary and overview, information selection and filtering, patient flow visualization, and geographical and longitudinal analyses. These case studies show that interactive data visualization techniques expand the boundary of data visualization as a pure presentation tool and bring certain analytical capability to support better healthcare decision making.

Interactive Data Visualization to Understand Data Better

2017 ◽  
pp. 27-36
Author(s):  
Zhecheng Zhu ◽  
Bee Hoon Heng ◽  
Kiok-Liang Teow
Keyword(s):  
Case Studies ◽  
Healthcare System ◽  
Data Visualization ◽  
Healthcare Systems ◽  
Multiple Data ◽  
Interactive Data ◽  
Interactive Map ◽  
Visual Impact ◽  
Visualization Techniques

This paper focuses on interactive data visualization techniques and their applications in healthcare systems. Interactive data visualization is a collection of techniques translating data from its numeric format to graphic presentation dynamically for easy understanding and visual impact. Compared to conventional static data visualization techniques, interactive data visualization techniques allow users to self-explore the entire data set by instant slice and dice, quick switching among multiple data sources. Adjustable granularity of interactive data visualization allows for both detailed micro information and aggregated macro information displayed in a single chart. Animated transition adds extra visual impact that describes how system transits from one state to another. When applied to healthcare system, interactive visualization techniques are useful in areas such as information integration, flow or trajectory presentation and location related visualization, etc. In this paper, three case studies are shared to illustrate how interactive data visualization techniques are applied to various aspects of healthcare systems. The first case study shows a pathway visualization representing longitudinal disease progression of a patient cohort. The second case study shows a dashboard profiling different patient cohorts from multiple perspectives. The third case study shows an interactive map illustrating patient geographical distribution at adjustable granularity. All three case studies illustrate that interactive data visualization techniques help quick information access, fast knowledge sharing and better decision making in healthcare system.

DUST: An interactive data visualization tool for selected atmospheric data

2000 ◽  
Vol 25 (8) ◽  
pp. 635-638 ◽  
Author(s):  
A Nölle ◽  
G Pfister ◽  
G Seckmeyer ◽  
H Wilhelms ◽  
M.L Richards ◽  
...  
Keyword(s):  
Data Visualization ◽  
Visualization Tool ◽  
Atmospheric Data ◽  
Interactive Data

scholarly journals Developing an Interactive Data Visualization Tool to Assess the Impact of Decision Support on Clinical Operations

2018 ◽  
Vol 31 (5) ◽  
pp. 640-645 ◽  
Author(s):  
Timothy C. Huber ◽  
Arun Krishnaraj ◽  
Dayna Monaghan ◽  
Cree M. Gaskin
Keyword(s):  
Decision Support ◽  
Data Visualization ◽  
Visualization Tool ◽  
Interactive Data ◽  
The Impact

scholarly journals Using Kaleidographic to visualize multimodal relations within and across texts

2018 ◽  
Vol 17 (4) ◽  
pp. 461-474 ◽  
Author(s):  
Helen Caple ◽  
Monika Bednarek ◽  
Laurence Anthony
Keyword(s):  
Discourse Analysis ◽  
Visualization Tool ◽  
News Values ◽  
Multimodal Discourse Analysis ◽  
Multimodal Discourse ◽  
Potential Applications ◽  
Media Platform ◽  
Interactive Data ◽  
Words And Images

Kaleidographic is a dynamic and interactive data visualization tool that allows users to observe and explore relations between any number of variables. It was developed in reaction to the problem of capturing the complex ways in which words and images combine to make meaning. This article introduces the Kaleidographic tool through a case study examining the multimodal construction of news values in news items widely shared on the Facebook social media platform. The design and functionality of the tool are explained in relation to the challenges faced when exploring both the visual and verbal elements of these news items as part of a multimodal discourse analysis. Through this case study, the authors show that Kaleidographic offers multimodal researchers a means of exploring relations at the intersection of different semiotic modes that might be missed in static graphs and tables. Despite Kaleidographic being initially conceived out of the analysis of text–image relations, the case study demonstrates that it has potential applications beyond multimodal discourse analysis. To facilitate broader applications of the tool, it is now publicly available online for use without charge.

Interactive Data Visualization Techniques Applied to Healthcare Decision Making

2015 ◽  
pp. 46-59 ◽  
Author(s):  
Zhecheng Zhu ◽  
Heng Bee Hoon ◽  
Kiok-Liang Teow
Keyword(s):  
Decision Making ◽  
Case Studies ◽  
Data Visualization ◽  
Capacity Planning ◽  
Healthcare Systems ◽  
Healthcare Decision ◽  
Healthcare Decision Making ◽  
Patient Profiling ◽  
Interactive Data ◽  
Visualization Techniques

Data visualization techniques are widely applied in all kinds of organizations, turning tables of numbers into visualizations for discovery, information communication, and knowledge sharing. Data visualization solutions can be found everywhere in healthcare systems from hospital operations monitoring and patient profiling to demand projection and capacity planning. In this chapter, interactive data visualization techniques are discussed and their applications to various aspects of healthcare systems are explored. Compared to static data visualization techniques, interactive ones allow users to explore the data and find the insights themselves. Four case studies are given to illustrate how interactive data visualization techniques are applied in healthcare: summary and overview, information selection and filtering, patient flow visualization, and geographical and longitudinal analyses. These case studies show that interactive data visualization techniques expand the boundary of data visualization as a pure presentation tool and bring certain analytical capability to support better healthcare decision making.

Interactive Data Visualization to Understand Data Better

2014 ◽  
Vol 4 (2) ◽  
pp. 1-10 ◽  
Author(s):  
Zhecheng Zhu ◽  
Bee Hoon Heng ◽  
Kiok Liang Teow
Keyword(s):  
Case Studies ◽  
Healthcare System ◽  
Data Visualization ◽  
Healthcare Systems ◽  
Data Set ◽  
First Case ◽  
Interactive Data ◽  
Visual Impact ◽  
Visualization Techniques

This paper focuses on interactive data visualization techniques and their applications in healthcare systems. Interactive data visualization is a collection of techniques translating data from its numeric format to graphic presentation dynamically for easy understanding and visual impact. Compared to conventional static data visualization techniques, interactive data visualization techniques allow users to self-explore the entire data set by instant slice and dice, quick switching among multiple data sources. Adjustable granularity of interactive data visualization allows for both detailed micro information and aggregated macro information displayed in a single chart. Animated transition adds extra visual impact that describes how system transits from one state to another. When applied to healthcare system, interactive visualization techniques are useful in areas such as information integration, flow or trajectory presentation and location related visualization, etc. In this paper, three case studies are shared to illustrate how interactive data visualization techniques are applied to various aspects of healthcare systems. The first case study shows a pathway visualization representing longitudinal disease progression of a patient cohort. The second case study shows a dashboard profiling different patient cohorts from multiple perspectives. The third case study shows an interactive map illustrating patient geographical distribution at adjustable granularity. All three case studies illustrate that interactive data visualization techniques help quick information access, fast knowledge sharing and better decision making in healthcare system.

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