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 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.

When Participation Wins Votes: Explaining the Emergence of Large-Scale Participatory Democracy

2021 ◽  
Author(s):  
Jared Abbott
Keyword(s):  
Case Studies ◽  
Political Party ◽  
Large Scale ◽  
Participatory Democracy ◽  
National Level ◽  
The Political ◽  
Political Costs ◽  
Participatory Institutions ◽  
Potential Benefits ◽  
Nationwide Implementation

Why are large-scale participatory institutions implemented in some countries but only adopted on paper in others? I argue that nationwide implementation of Binding Participatory Institutions (BPIs)––a critical subtype of participatory institutions––is dependent on the backing of a strong institutional supporter, often a political party. In turn, parties will only implement BPIs if they place a lower value on the political costs than on the potential benefits of implementation. This will be true if: 1) significant societal demand exists for BPI implementation and 2) the party’s political opponents cannot take advantage of BPIs for their own gain. I test this theory through two detailed case studies of Venezuela and Ecuador, drawing on 165 interviews with key national-level actors and grassroots activists.

scholarly journals Strategic management applied to the Six-Sigma suitability appraisal for R&D in FMCG companies

2016 ◽  
Vol 2 (1) ◽  
pp. 80-99
Author(s):  
Davidson Lütkenhaus ◽  
Marcella Nunes De Freitas
Keyword(s):  
Six Sigma ◽  
Large Scale ◽  
Multinational Companies ◽  
Main Concern ◽  
Cultural Changes ◽  
Time Saving ◽  
Web Based ◽  
Strategic Implementation ◽  
Potential Benefits ◽  
New System

This research assesses the suitability of the Six-sigma program for R&D in FMCG companies. The study also includes an analysis of its potential advantages and challenges for this business area. This was performed through data acquisition using a web-based survey targeting large scale multinational companies. Results showed that most R&D personnel within FMCG companies see Six-sigma as a positive methodology for their sector. Roughly 80% of the participants selected time saving and better knowledge allocation as the main advantages of the Six-sigma system. Almost 90% of the survey contributors believe that the series of potential benefits could lead to important scientific breakthroughs. A financial challenge is expected with the implementation and it was said to be the main concern of R&D personnel, especially from those with managerial backgrounds. Cultural changes and scientific obstacles were not reported as imminent threats to the new system. In light of the above, Six-sigma was found to be suitable for R&D in FMCG companies requiring only a few modifications in its standards and a well-defined strategic implementation plan.

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.

Randomized trial of a web-based intervention to address barriers to clinical trials.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 6500-6500 ◽  
Author(s):  
Neal J. Meropol ◽  
Terrance Lynn Albrecht ◽  
Yu-Ning Wong ◽  
Al Bowen Benson ◽  
Joanne S. Buzaglo ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Decision Making ◽  
Clinical Trials ◽  
Randomized Trial ◽  
Large Scale ◽  
College Education ◽  
Phase Iii ◽  
Post Intervention ◽  
Web Based ◽  
Attitudinal Barriers

6500 Background: Cancer patients (pts) have knowledge and attitudinal barriers to participation in clinical trials (CT). We developed PRE-ACT (Preparatory Education About Clinical Trials), a tailored, interactive, web-based intervention to address these barriers and improve preparation for consideration of CT as a treatment option. Methods: We conducted a prospective, randomized, multicenter, phase III clinical trial of PRE-ACT vs. control (general text about CT excerpted from NCI materials). All assessments and interventions were conducted online. Cancer pts >18 years old were enrolled before initial oncologist consultation. Pts completed a baseline assessment including CT knowledge (19-item); CT attitudes (28-item); preparation for decision making (10-item); and validated measures of preferences for shared decision making and quality/length of life. PRE-ACT pts received a summary of their preferences and a list of their top CT barriers. Based on ranking of individual barriers, pts were presented with a video library of 30-90 second clips addressing their top barriers (10 maximum). After the educational intervention a follow up survey reassessed CT barriers and preparation. Results: 1255 pts were randomized; median age 59 (range 20-88); 58% female; 12% non-white / 2% Hispanic; 76.4% some college education. 1081 pts completed baseline and post-intervention assessments. The control and PRE-ACT groups both had improved knowledge, reduced attitudinal barriers, and improved preparation (p<.0001 for all comparisons). PRE-ACT was more effective than control in improving knowledge (p=.0006) and attitudes (p<.0001). Furthermore, pts in the PRE-ACT arm were more satisfied with the amount (p=.002) and format (<.0001) of information, and felt more prepared to consider CT (p=.0003). Conclusions: This large-scale randomized trial of a tailored, web-based, video intervention demonstrates that educational information delivered online before the oncologist visit can significantly reduce knowledge barriers and attitudinal barriers and improve preparation for consideration of clinical trials. Both text and PRE-ACT are effective, with greater improvements and satisfaction in the PRE-ACT group. Clinical trial information: NCT00750009.

Large-Scale Integrated Academic Portals

2011 ◽  
pp. 538-546
Author(s):  
Paolo Bellavista
Keyword(s):  
Large Scale ◽  
Network Connectivity ◽  
The Internet ◽  
Web Based ◽  
Telecommunication Systems ◽  
Web Information ◽  
University Communities ◽  
Potential Benefits ◽  
Widespread Availability ◽  
Fixed Wireless

The increasing availability of fixed/wireless network connectivity and the integration of telecommunication systems and the Internet create novel opportunities for users who can benefit from anytime-anywhere access to a growing amount of Internet/intranet Web information. In particular, university communities clearly perceive the potential benefits of widespread availability of Web-based services, which should satisfy heterogeneous requirements from different classes of users, for example, students, teachers, administrative and technical staffs.

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

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.

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.

scholarly journals i2dash: Creation of Flexible, Interactive and Web-based Dashboards for Visualization of Omics-pipeline Results

2020 ◽  
Author(s):  
Arsenij Ustjanzew ◽  
Jens Preussner ◽  
Mette Bentsen ◽  
Carsten Kuenne ◽  
Mario Looso
Keyword(s):  
Single Cell ◽  
Data Visualization ◽  
Large Scale ◽  
R Package ◽  
Cloud Services ◽  
Sequencing Analysis ◽  
Omics Data ◽  
Web Based ◽  
Automated Data Processing ◽  
Generic Design

AbstractData visualization and interactive data exploration are important aspects of illustrating complex concepts and results from analyses of omics data. A suitable visualization has to be intuitive and accessible. Web-based dashboards have become popular tools for the arrangement, consolidation and display of such visualizations. However, the combination of automated data processing pipelines handling omics data and dynamically generated, interactive dashboards is poorly solved. Here, we present i2dash, an R package intended to encapsulate functionality for programmatic creation of customized dashboards. It supports interactive and responsive (linked) visualizations across a set of predefined graphical layouts. i2dash addresses the needs of data analysts for a tool that is compatible and attachable to any R-based analysis pipeline, thereby fostering the separation of data visualization on one hand and data analysis tasks on the other hand. In addition, the generic design of i2dash enables data analysts to generate modular extensions for specific needs. As a proof of principle, we provide an extension of i2dash optimized for single-cell RNA-sequencing analysis, supporting the creation of dashboards for the visualization needs of single-cell sequencing experiments. Equipped with these features, i2dash is suitable for extensive use in large scale sequencing/bioinformatics facilities. Along this line, we provide i2dash as a containerized solution, enabling a straightforward large-scale deployment and sharing of dashboards using cloud services.i2dash is freely available via the R package archive CRAN.

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