Interactive Data Visualization to Understand Data Better

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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Application of Geographical Information System and Interactive Data Visualization in Healthcare Decision Making

Decision Management ◽

10.4018/978-1-5225-1837-2.ch057 ◽

2017 ◽

pp. 1244-1254

Author(s):

Zhecheng Zhu

Keyword(s):

Decision Making ◽

Information System ◽

Data Visualization ◽

Healthcare Services ◽

Geographical Information ◽

Multiple Data ◽

Interactive Data ◽

Visual Impact ◽

Site Planning ◽

Visualization Techniques

This paper focuses on two techniques and their applications in healthcare systems: geographic information system (GIS) and interactive data visualization. GIS is a type of technique applied to manipulate, analyze and display spatial information. It is a useful tool tackling location related problems. GIS applications in healthcare include evaluation of accessibility to healthcare facilities, site planning of new healthcare services and analysis of risks and spreads of infectious diseases. 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 user 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. One area both techniques intersect is location analysis. In this paper, real life case studies will be given to illustrate how these two techniques, when combined together, help in solving quantitative or qualitative location related problem, visualizing geographical information and accelerating decision making procedures.

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Interactive Data Visualization Techniques Applied to Healthcare Decision Making

Decision Management ◽

10.4018/978-1-5225-1837-2.ch052 ◽

2017 ◽

pp. 1157-1171 ◽

Cited By ~ 2

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.

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Interactive Data Visualization Techniques Applied to Healthcare Decision Making

Big Data Analytics in Bioinformatics and Healthcare - Advances in Bioinformatics and Biomedical Engineering ◽

10.4018/978-1-4666-6611-5.ch003 ◽

2015 ◽

pp. 46-59 ◽

Cited By ~ 2

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.

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Application of Geographical Information System and Interactive Data Visualization in Healthcare Decision Making

International Journal of Big Data and Analytics in Healthcare ◽

10.4018/ijbdah.2016010104 ◽

2016 ◽

Vol 1 (1) ◽

pp. 49-58 ◽

Cited By ~ 1

Author(s):

Zhecheng Zhu

Keyword(s):

Decision Making ◽

Information System ◽

Data Visualization ◽

Spatial Information ◽

Real Life ◽

Geographical Information ◽

Data Set ◽

Interactive Data ◽

Visual Impact ◽

Visualization Techniques

This paper focuses on two techniques and their applications in healthcare systems: geographic information system (GIS) and interactive data visualization. GIS is a type of technique applied to manipulate, analyze and display spatial information. It is a useful tool tackling location related problems. GIS applications in healthcare include evaluation of accessibility to healthcare facilities, site planning of new healthcare services and analysis of risks and spreads of infectious diseases. 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 user 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. One area both techniques intersect is location analysis. In this paper, real life case studies will be given to illustrate how these two techniques, when combined together, help in solving quantitative or qualitative location related problem, visualizing geographical information and accelerating decision making procedures.

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Visualizing Sixteen Years of Data About Portuguese Leisure-Cultural Activities

International Journal of Creative Interfaces and Computer Graphics ◽

10.4018/jcicg.2012070102 ◽

2012 ◽

Vol 3 (2) ◽

pp. 8-22

Author(s):

Clarissa Rodrigues ◽

Elizabeth Carvalho

Keyword(s):

Data Visualization ◽

Visual Cues ◽

Leisure Time ◽

Visual Representations ◽

End User ◽

Cultural Activities ◽

Interactive Data ◽

Visualization Techniques ◽

Visualization Application

This paper describes an interactive data visualization application that aims to show how the Portuguese people spent culturally their leisure time between 1994 and 2009. The leisure trend is displayed to the end-user through the use of different visualization techniques and visual cues. The authors developed the visual representations based on the use of simple and regular visual shapes that could be easily combined, interpreted, memorized and used. To better evaluate their results, the authors tested their prototype against a preselected group of subjects.

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

Water ◽

10.3390/w12102928 ◽

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.

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Kaleidographic

International Journal of Corpus Linguistics ◽

10.1075/ijcl.18038.cap ◽

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.

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Interactive Data Visualization: New Directions for Accounting Information Systems Research

Journal of Information Systems ◽

10.2308/jis.2010.24.2.1 ◽

2010 ◽

Vol 24 (2) ◽

pp. 1-37 ◽

Cited By ~ 52

Author(s):

William Dilla ◽

Diane J. Janvrin ◽

Robyn Raschke

Keyword(s):

Data Visualization ◽

Enterprise Resource Planning ◽

Balanced Scorecard ◽

Accounting Information ◽

Resource Planning ◽

Systems Research ◽

Interactive Data ◽

Visualization Techniques ◽

The Impact ◽

The Relationship

ABSTRACT: Many companies today utilize interactive data visualization to present accounting information to external users on their investor relations websites and to internal users in applications such as enterprise resource planning, Balanced Scorecard, network security, and fraud detection systems. We develop a taxonomy for examining the current state of interactive data visualization research related to accounting decision making. We organize our review around three themes: the relationship between task characteristics and interactive data visualization techniques, the relationship between decision maker characteristics and interactive data visualization techniques, and the impact of interactive data visualization techniques on decision processes and outcomes. The review categorizes relevant research, describes the research questions addressed, and suggests avenues for further research.

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A Comprehensive Survey on Data Utility and Privacy: Taking Indian Healthcare System as a Potential Case Study

Inventions ◽

10.3390/inventions6030045 ◽

2021 ◽

Vol 6 (3) ◽

pp. 45

Author(s):

Prathamesh Churi ◽

Ambika Pawar ◽

Antonio-José Moreno-Guerrero

Keyword(s):

Healthcare System ◽

Large Population ◽

Healthcare Systems ◽

Healthcare Management ◽

Healthcare Sector ◽

Sensitive Data ◽

Data Breaches ◽

Healthcare Data ◽

Privacy Issues

Background: According to the renowned and Oscar award-winning American actor and film director Marlon Brando, “privacy is not something that I am merely entitled to, it is an absolute prerequisite.” Privacy threats and data breaches occur daily, and countries are mitigating the consequences caused by privacy and data breaches. The Indian healthcare industry is one of the largest and rapidly developing industry. Overall, healthcare management is changing from disease-centric into patient-centric systems. Healthcare data analysis also plays a crucial role in healthcare management, and the privacy of patient records must receive equal attention. Purpose: This paper mainly presents the utility and privacy factors of the Indian healthcare data and discusses the utility aspect and privacy problems concerning Indian healthcare systems. It defines policies that reform Indian healthcare systems. The case study of the NITI Aayog report is presented to explain how reformation occurs in Indian healthcare systems. Findings: It is found that there have been numerous research studies conducted on Indian healthcare data across all dimensions; however, privacy problems in healthcare, specifically in India, are caused by prevalent complacency, culture, politics, budget limitations, large population, and existing infrastructures. This paper reviews the Indian healthcare system and the applications that drive it. Additionally, the paper also maps that how privacy issues are happening in every healthcare sector in India. Originality/Value: To understand these factors and gain insights, understanding Indian healthcare systems first is crucial. To the best of our knowledge, we found no recent papers that thoroughly reviewed the Indian healthcare system and its privacy issues. The paper is original in terms of its overview of the healthcare system and privacy issues. Social Implications: Privacy has been the most ignored part of the Indian healthcare system. With India being a country with a population of 130 billion, much healthcare data are generated every day. The chances of data breaches and other privacy violations on such sensitive data cannot be avoided as they cause severe concerns for individuals. This paper segregates the healthcare system’s advances and lists the privacy that needs to be addressed first.

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