Data Visualization in Health
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The document details a data visualization workshop on the global burden of disease, highlighting the vital role of visual analytics in understanding complex data. It emphasizes how visual tools enhance decision-making and communication by transforming abstract information into comprehensible visual formats. Additionally, it discusses various data visualization platforms and tools, showcasing examples from IHME and PAHO for effective data analysis and storytelling.
![What is data visualization?
• Data visualization is the graphical display of
abstract information for sense-making or data
analysis, and communication in a way that leads to
understanding for action.
• Its goal is to visualize data in a way that leads to
understanding.
[Stephen Few, 2014]
• Data visualization is a fundamental product from
the Visual analytics process
10](https://image.slidesharecdn.com/datavisualizationinhealth-150903164414-lva1-app6891/85/Data-Visualization-in-Health-11-320.jpg)
Data Visualization in Health
- 1. Data Visualization Workshop on Global Burden of Disease Big Data and Scientific Computation FIOCRUZ, Rio de Janeiro, Brazil, August 25-27, 2015 Ramon Martinez Technical Adviser in Health Metrics martiner@paho.org @HlthAnalysis
- 2. Contents • Data Visualization • Data Visualization Tools • Data Analytics and Visualization Platforms o IHME Visualization Platform o PAHO Visualization Platform 1
- 3. Why data visualization? • There is an amazing connection between human visual sensors and the brain • Humans have an extraordinary visual capacity to detect patterns 2
- 4. Visual perception • How many nines (9) are in this matrix? 3
- 5. Visual perception • How many nines (9) are in this matrix? 4
- 6. Visual perception • Can you see any pattern in this table? 5
- 7. Visual perception • Can you see any pattern in this graph? Title of the Presentation6
- 8. Statistics and Graphs • Four distinct datasets • Each with statistics properties that are essentially identical Title of the Presentation7 Mean of x = 9.0 Mean of y = 7.5 Variance of x = 11 Variance of y = 4.13 Nearly identical correlation and regression line Ascombe’s Quartet
- 9. Statistics and Graphs 8 • Four distinct datasets • Each with statistics properties that are essentially identical • But when plotted, they suddenly appear very different • Ascombe suggested the combined use of graphs and statistics methods in data analysis Ascombe’s Quartet
- 10. Why data visualization? • People make better decisions when they’re based on understanding. • For information to be understood, it must often be presented in visual form because patterns, trends, and outliers require a picture for the human brain to see and comprehend. • Data visualization is essential for: o Data exploration and understanding o communicating data o making better decisions 9
- 11. What is data visualization? • Data visualization is the graphical display of abstract information for sense-making or data analysis, and communication in a way that leads to understanding for action. • Its goal is to visualize data in a way that leads to understanding. [Stephen Few, 2014] • Data visualization is a fundamental product from the Visual analytics process 10
- 12. What is visual analytics? • Visual analytics is the science of analytical reasoning supported by interactive visual interfaces. • Visual Analytics methods allow people to combine: 11 human flexibility, creativity, and background knowledge today’s IT capacities for data storage, processing, and visualiziattion + to gain insight and make well-informed decisions in complex problems =
- 13. The analytic process 1. The research question – public health situation 2. Define the analytic framework 3. Identification of data sources 4. Create the analytic plan - methods 5. Conduct analysis & interpretation of results 6. Communicate results and findings - storytelling 7. Propose interventions – actions for improving health 12
- 14. The Cycle of Visual Analytic 13 When people are exploring and analyzing data, they enter into an iterative and non-linear cycle of 1. data acquisition, 2. selection of visual structures 3. instantiate data views (graphs, visual forms) 4. analysis and synthesis, hypothesis building 5. sharing and re- examination where at any point they may need to skip steps, back-up, seek additional data, or even start over. Diagram adapted from the cycle of visual analytic diagram. Pat Hanrahan, Chris Stolte and Jock MacKinlay. Visual Analysis for Everyone. Whitepaper. Tableau Software, Inc., 2007 http://www.tableau.com/sites/default/files/whitepapers/visual-analysis-for- everyone.pdf
- 15. From Data To Visualization 14
- 16. Data visualization tools • There is a constellation of tools for visualizing data o DATAVISUALIZATION.CH selected tools: http://selection.datavisualization.ch/ o Andy Kirk’s visualization resources: http://www.visualisingdata.com/resources/ 15
- 17. Data visualization tools • Libraries o Libraries for adding charts and visualization capabilities to applications o Required programming or coding. Suitable for software developers o Use Programming Language directives to connect to data sources • Web-based tools o Visualization tools on the web o Easy to use, no programing required o Datasets should be upload. Suitable for small-medium datasets • Data Analytics and Visualization Platform o is an enterprise-class (complete) solution that provides the tools and methods for: 1. connect to most of the DBMS standards (SQL, Web services, local files, etc.) 2. to data exploration and visual analytics, 3. creation and design of data visualizations and dashboards, and 4. capability for team collaboration and content sharing, and dissemination o None or minimum programming required o Self-service approach, empower business users. 16
- 18. Visual Analytics & Visualization Platform: high level system architecture Title of the Presentation17 Source systems / Data sources Data preparation and integration Data storage & managements Data discovery & visual analytics Web-based apps / services for data dissemination Data cleansing, transformation, processing, preparation and integration processes (workflows & scheduling) DBMS: Data repository with data (internal and external) ready for analysis and visualizations Visual discovery and analytic tools and methods. Data computation. Data visualization sharing and collaboration Mortality Health Survey Diagram adapted from BI/DW technical system architecture Hospital records PH surveillance Population GBD Visualizations Open Data Portal Research Collaboration site MoH Web site
- 19. Technology Components • Three integral technology components to achieve analytic and visualization o Agile data warehouse solution o Data preparation and integration software o Visualization and advanced visual analytics solution o Content Management System Title of the Presentation18
- 20. IHME GBD Visualization Platform • IHME implemented in-house custom-software development to create Data Visualizations • Development team + collaboration w/ researchers and data analysts o 1 Product Owner, Data Visualization o 1 Data Visualization Scientist o 3 JavaScript Developers • Development tools: o JavaScript - programming language o jQuery - development framework for JavaScript web-based applications o D3.js - graphics library o HTML & CSS - hypertext markup language and style sheet for development and design of web pages Title of the Presentation19
- 21. IHME GBD Visualization Platform Title of the Presentation20 http://www.healthdata.org/results/data-visualizations
- 22. PAHO Visualization Platform • PAHO selected off-the-shelf commercial solutions for analytics and data visualizations • Data analysts and health professionals from technical areas are empower to do self-service analysis and produce data visualizations • Visual Analytics and Visualization Platform: o MS SQL Server - database/data warehouse o Alteryx - data integration and advance analytics software o Tableau - visual analytics and visualization software o Joomla - content management system (CMS) / PAHO Web site o MS SharePoint - content management system for Intranet and collaboration sites 21
- 23. PAHO Visualization Platform Title of the Presentation22
Editor's Notes
- #9: In 1973, Francis J. Anscombe published a paper titled, Graphs in Statistical Analysis. The idea of using graphical methods had been established relatively recently by John Tukey, but there was evidently still a lot of skepticism. Anscombe first lists some notions that textbooks were “indoctrinating” people with, like the idea that “numerical calculations are exact, but graphs are rough.” He then presents a table of numbers. It contains four distinct datasets (hence the name Anscombe’s Quartet), each with statistical properties that are essentially identical: the mean of the x values is 9.0, mean of y values is 7.5, they all have nearly identical variances, correlations, and regression lines (to at least two decimal places).
- #13: Visual Analytics Visual analytics is the science of analytical reasoning supported by interactive visual interfaces. Visual Analytics methods allow people to combine human flexibility, creativity, and background knowledge with today’s computers capacities for data storage and processing allowing them to gain insight and make well-informed decisions in complex problems. the complex nature of any problem makes it indispensable to include human intelligence in the data analysis process. human flexibility, creativity, and background knowledge with the enormous storage and processing capacities of today’s computers to gain insight into complex problems. Using advanced visual interfaces, humans may directly interact with the data analysis capabilities of today’s computer, allowing them to make well-informed decisions in complex situations. Thomas, J., Cook, K.: Illuminating the Path: Research and Development Agenda for Visual Analytics. IEEE-Press (2005)
- #15: The creation and design of data visualization is an iterative and non-linear cycle of data acquisition, selection of visual structures and display of graphs (visual forms), analysis and synthesis, hypothesis building, sharing and re-examination
- #17: Selected Data Visualization Tools and Resources DATAVISUALIZATION.CH selected tools: http://selection.datavisualization.ch/ Andy Kirk’s Visualization Resources: http://www.visualisingdata.com/resources/
- #20: C