Abstract:
Data Visualization describes the process of transferring data into images on the computer. Only using images, humans are able to get insights into large amounts of data - which makes data visualization a very important part of data analytics. However, there are a lot of techniques and tools available - and which ones are suited best for which tasks? Also, the process of creating a data visualization, selecting the right visual mappings, colors, chart types, etc, is very complex and can also confuse viewers, if not done properly. In this talk, I will reflect on current developments in data visualization research and how data visualization can be used in a data science workflow.
Speaker Bio:
Dr. Johanna Schmidt is head of the research unit “Visual Analytics” at VRVis Zentrum für Virtual Reality und Visualisierung Forschungs-GmbH in Vienna. She received her Master’s degree in Computer Science and afterward continued with a Ph.D. in data visualization at TU Vienna, Austria. Her current research focuses on the visual analysis of large datasets, mainly manufacturing data originating from industry companies and time series data. Additionally, she is a lecturer at the TU Vienna and at the FH Salzburg.
https://www.meetup.com/de-DE/predictive-analytics-for-industry-4-0/
1. What is data visualization, and how to
integrate it in a data science workflow?
Johanna Schmidt
VRVis Research Center
Vienna, Austria
2. Johanna Schmidt Predictive Analytics for Industry 4.0
Data Visualization
2
http://vda-lab.github.io/2019/12/vegalite
3. Johanna Schmidt Predictive Analytics for Industry 4.0
Data Visualization
3
https://powerbi.microsoft.com/en-za/blog/power-bi-on-the-go/
4. Johanna Schmidt Predictive Analytics for Industry 4.0
Data Visualization
4
https://blog.iao.fraunhofer.de/daten-retten-leben-corona-ausbreitung-endlich-verstaendlich-und-in-echtzeit/
5. Johanna Schmidt Predictive Analytics for Industry 4.0
Data Visualization
5
https://datavis-online.github.io/organisation.html
6. Johanna Schmidt Predictive Analytics for Industry 4.0
VRVis Fast Facts
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Research Center
Founded in 2000 as Center
Since 2010 financed by in
Mission: R&D in Visual Computing
Data visualization, Visual Analytics, AI, Data Science
Connection between Science and Industry
Legal organization: GmbH, Non-profit
Ares Tower in Vienna, 1220 and TU-Graz, 8010 Graz
Budget von ~7 M€ (2019), ~70 Employees
8. Johanna Schmidt Predictive Analytics for Industry 4.0
Visual Data Analysis
8
https://de.wikipedia.org/wiki/Anscombe-Quartett
9. Johanna Schmidt Predictive Analytics for Industry 4.0
Visual Data Analysis
9
https://de.wikipedia.org/wiki/Anscombe-Quartett
10. Johanna Schmidt Predictive Analytics for Industry 4.0
Visual Data Analysis
10
https://de.wikipedia.org/wiki/Anscombe-Quartett
11. Johanna Schmidt Predictive Analytics for Industry 4.0
Visual Data Analysis
11
https://www.autodesk.com/research/publications/same-stats-different-graphs
13. Johanna Schmidt Predictive Analytics for Industry 4.0
Data Visualization Techniques
13
Different Types of Data
Uni- to multivariate Data
Complex datasets require complex representations
Data Visualization Research
New data visualization techniques
Interaction techniques
Summarization/aggregation
14. Johanna Schmidt Predictive Analytics for Industry 4.0
Data Visualization Techniques
14
Different Types of Data
Univariate Data
https://upload.wikimedia.org/wikipedia/commons/1/1d/Example_histogram.png
15. Johanna Schmidt Predictive Analytics for Industry 4.0
Data Visualization Techniques
15
Different Types of Data
Univariate Data
Bivariate Data
https://en.wikipedia.org/wiki/Scatter_plot
16. Johanna Schmidt Predictive Analytics for Industry 4.0
Data Visualization Techniques
16
Different Types of Data
Univariate Data
Bivariate Data
Trivariate Data
https://i.stack.imgur.com/6kFx8.png
17. Johanna Schmidt Predictive Analytics for Industry 4.0
Data Visualization Techniques
17
Different Types of Data
Univariate Data
Bivariate Data
Trivariate Data
Multivariate Data
http://i.imgur.com/ggQMO8z.png
18. Johanna Schmidt Predictive Analytics for Industry 4.0
Data Visualization Techniques
18
Different Types of Data
Univariate Data
Bivariate Data
Trivariate Data
Multivariate Data
http://www.unige.ch/ses/sococ/cl/r/scatmat.e.html
19. Johanna Schmidt Predictive Analytics for Industry 4.0
Data Visualization Techniques
19
Different Types of Data
Univariate Data
Bivariate Data
Trivariate Data
Multivariate Data
https://harmoniccode.blogspot.com/2018/02/friday-fun-lix-parallel-coordinates.html
20. Johanna Schmidt Predictive Analytics for Industry 4.0
Data Visualization Techniques
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Different Types of Data
Univariate Data
Bivariate Data
Trivariate Data
Multivariate Data
http://www.corentindupont.info/blog/posts/Others/2015-09-18-no-spider.html
21. Johanna Schmidt Predictive Analytics for Industry 4.0
Data Visualization Techniques
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Chart Suggestions
From Data to Viz
https://www.data-to-viz.com/
22. Johanna Schmidt Predictive Analytics for Industry 4.0
Data Visualization Techniques
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Chart Suggestions
Data Visualization Catalogue
https://datavizcatalogue.com/search.html
23. Johanna Schmidt Predictive Analytics for Industry 4.0
Data Visualization in Predictive Analytics
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Analytics Workflow
Several steps necessary
How to integrate data visualization?
24. Johanna Schmidt Predictive Analytics for Industry 4.0
Data Visualization in Predictive Analytics
24
Jeffrey Heer, Capstone Talk EuroVis 2019: http://eurovis2019.tecnico.ulisboa.pt/wp-content/uploads/2019/06/EuroVis2019-Capstone.pdf
31. Johanna Schmidt Predictive Analytics for Industry 4.0
Model / Evaluate
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Data Exploration
Understanding data structure
Detect new patterns
-> DEMO
33. Johanna Schmidt Predictive Analytics for Industry 4.0
Model / Evaluate
33
Regression Feature Evaluation
Understand variable influence
Evaluate model prediction results
34. Johanna Schmidt Predictive Analytics for Industry 4.0
Model / Evaluate
34
Regression Feature Evaluation
Understand variable influence
Evaluate model prediction results
-> DEMO
35. Johanna Schmidt Predictive Analytics for Industry 4.0
Model / Evaluate
35
Evaluation of AI Model Results
Understand relation between input and parameters
Avoid over/underfitting
Study model bias
-> Explainable AI
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Explainable AI
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https://distill.pub/2018/building-blocks/
37. Johanna Schmidt Predictive Analytics for Industry 4.0
Explainable AI
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http://playground.tensorflow.org
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Explainable AI
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“What-If Tool” by Google
https://ai.googleblog.com/2018/09/
the-what-if-tool-code-free-probing-of.html
42. Johanna Schmidt Predictive Analytics for Industry 4.0
Tools
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Data Visualization Tools
Programming libraries
Standalone / web-based applications
43. Johanna Schmidt Predictive Analytics for Industry 4.0
Tools
https://source.opennews.org/articles/what-i-learned-recreating-one-chart-using-24-tools/
45. Johanna Schmidt Predictive Analytics for Industry 4.0
https://www.cxtoday.com/data-analytics/gartner-magic-quadrant-for-analytics-and-business-intelligence-platforms-2022/
46. What is data visualization, and how to
integrate it in a data science workflow?
Johanna Schmidt
VRVis Research Center
Vienna, Austria