Project ideas
These are some random ideas that may be fun to pursue.
- The crime statistics of Bloomington (and other cities in Indiana): https://bloomington.in.gov/public-safety/annual-reports
- Bloomington crash data visualization: https://specials.idsnews.com/car-crash-dashboard-monroe-county/
- Land use of transportation modes (see also https://whatthestreet.com)
- Finance of transportation - budget analysis visualization
- Parking visualization: city parking stock
- IU parking stock visualization
- Bike parking visualization
- Parking utilization visualization
- Residential parking zone visualization
- Scooter routes and availability visualization
- Bike counter data analysis
- Rate of ownership and rental in each neighborhood
- Neighbor association
- Visualization of IU/Bloomington trees
- A tool to visualize parking lots of a given region by analyzing the open street map data (see https://twitter.com/the_transit_guy/status/1572971758189252609)
- Can you make a series of short videos and tweets that effectively communicate a concept with data visualization?
- Implement Euler diagram and visualize vaccine efficacy data: see https://bsky.app/profile/rmcelreath.bsky.social/post/3kcl6ssl3mn2j and https://bsky.app/profile/rmcelreath.bsky.social/post/3kcnmbyiynh2x
- Visualizing uncertainties: There have been some innovative attempts to visualize the uncertainty in the data. For instance, this map visualization animates many resampled results to show the uncertainty in the data. This technique uses ambiguous colors. See also Visualizing uncertainty.
- Creating educational animations: You can pick a challenging mathematical (statistical) concept and create an animation that effectively explains it. See https://simplystatistics.org/2017/08/08/code-for-my-educational-gifs/ as examples and source code.
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Now there exist many apps that display personal data. For instance, Apple Health or Strava visualizes your heart rate during the exercise session. It would be interesting to write a critique on some of these visualizations (for instance, there are lots of issues with Apple Health's visualizations) and create an 'improved' visualizations that address the shortcomings of existing ones.
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The data from yourself would be interesting for you and you can try various visualizations of your personal data. Even a simple heart rate dataset can be interesting when combined with other information.
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Map projections: An interactive (or animated) visualization that reveals how each map projection distorts reality. For instance, this visualization on Mercator projection shows how much Mercator projection distorts the area. An improved version of this or more general visualization for other projections would be interesting.
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Weather maps: there are nice examples of wind maps: http://hint.fm/wind/ and https://earth.nullschool.net. Can there be other real-time weather patterns that can be visualized?
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Visualizing UN peacekeeping actions: https://peacekeeping.un.org/en/peacekeeping-master-open-datasets
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Visualizing earthquakes. This visualization of 2011 Japan earthquakes can be inspiring.
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Mapping America’s wicked weather and deadly disasters - beautiful rendering of high-resolution weather data.
One of the IU's grand challenge projects is "Prepared for Environmental Change". They are dealing with large datasets about environmental changes, including wildlife, farming, climates, and so on. If you are interested in, take a look at their research projects (https://eri.iu.edu/understand/research-projects/index.html) and contact Justin Peters at jppeters@iu.edu. YY will also be happy to discuss.
Explorables are usually interactive visualizations of mathematical or computational models where you can explore the model by playing with parameters and watching how they change the behaviors of the models. You can find some interesting models, algorithms, or equations and create a nice explorable. See Visualizing mathematics and statistics, Visualizing algorithms, and http://www.complexity-explorables.org/explorables/
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Map equation is a very nice framework for detecting network communities. The visualization was written in Flash: http://www.mapequation.org/apps/MapDemo.html Translating this into Javascript can be a nice project.
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Link community detection is a method for detecting highly overlapping communities. There was an interactive visualization written in Flex. Translating this into Javascript can be a nice project.
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It is quite difficult to understand how Deep Neural Networks work. Using visualization to study what and how they learn would be fascinating.
See Visualizing algorithms. You can create an (interactive) website that visually explains a complex algorithm step by step.
- There are lots of interesting datasets and visualizations for music. See Music visualization for inspiration.
- Analysis of Bollywood movies: https://github.com/pncnmnp/TIMDB/