Final deliverable due May 3 CS 6730 - Data Visualization Spring 2021

Design Project

A summary of some top projects from this 2021 spring class.

This document describes the capstone project for the course. Students will work on a project in teams of 2 people.

The idea of the project is to take the knowledge and background that you are learning this semester about data visualization and put it to good use in a new, creative effort. A real key to the project, however, is to select a data set that people will find interesting and intriguing. Even better would be to select a data set with a clearly identified set of "users," "analysts", or "consumers" who care deeply about that data. Select a topic that people want to know more about! I cannot emphasize strongly enough the importance of your topic and data set.

No matter what topic you choose, I am expecting a high-quality project. In particular, I'm seeking creative projects showcasing interesting ideas. A good project should consist of an effective visualization design and an implementation of the design using some visualization system.

You are free to choose any visualization tool or tools that you want in order to help create your visualization. Since we are studying Tableau this term, it might be a good choice. Note that you can even use a combination of tools.

You will have five main milestones or deliverables. First, you must form your team. Second, you must select a topic and data set. Third, your team will have a midterm project review and critique with the professor and TAs. Fourth, you will give a short explanation/demonstration of your project to the instructor and TAs during final exam week. Finally, you will create a video (3 minutes or less) that explains your visualizations and shows it in action. All teams will show their videos in our "Video Extravaganza" during the class' final exam period.

Important Milestones

  • Mar 17 - Team formation. If you know your partner, the two members of your team should list your names on the Canvas page for the Project. If you don't have a partner, email Prof. Stasko and he will pair you up with another student.

  • Mar 26 - Initial project description. 1-2 page document listing project members and describing topic to be addressed and data sources/formats. You should address the following questions: Make sure to describe the data and its attributes in detail. Show a snippet from your data. I do encourage teams to run their ideas by Prof. Stasko before turning in this milestone. We will get initial feedback to teams by the following Tuesday. In some cases, we will recommend changing topic. If that occurs, we encourage the team to develop a new topic as soon as possible.

  • Week of Apr. 8-14 - Midterm Design Review & Critique. This is an opportunity for you to show what you have accomplished so far and to receive feedback about the project's progress. You should create and show a variety of design ideas for the data set and topic you have chosen. This is an opportunity for your team to be creative and come up with a variety of ideas. Be ready to answer questions about the purpose of the visualization system and who the users will be. Provide a list of analytic questions and queries that a person should be able to answer using this visualization. Finally, you should explain your plan for creating the visualization and how you will approach that. This milestone may involve a short report and/or a short meeting with the instructor and TAs. More details to come.

  • Apr 28-29 - Project presentation/demonstration. Each team will meet with the instructor and TAs to show and explain their visualization and describe what they have done. You will need to submit through Canvas and bring three copies to the meeting of a 1-page project overview document. The document should include the following items: topic, team member names, screen shot, problem description & project overview (1 paragraph).

  • Apr 30 - Project materials. Each team will submit all their project files (Tableau projects, webpages, pdf's, etc.) to a Canvas assignment. Include in this package a one-page overview document of the project and the files being submitted.

  • May 3 - System video. Create a 3 minute or less video that describes the problem you addressed and that showcases your visualization. During our final exam period, we will have a "Video Showcase" where each team presents its video and has a few minutes available to answer questions about it. You will need to provide a link to the video file to the instructor by midnight on May 3, the day before. Do NOT email the actual large video file--Instead, submit it through a Canvas assignment. Use mp4 format on the video at least 720p but not bigger than 1080p.


    Once your topic has been chosen, each team is required to meet 1-1 with one of the TAs or the Professor at least once. This can be a very valuable opportunity for you to get feedback about your design and implementation. Failure to follow this requirement will result in points being deducted from your project score.

    To determine your grade for the project, we will evaluate the overall quality of your project, including all milestones and components. It is important that you make progress on the project quickly. This is doubly beneficial as it allows more time for your implementation.

    The following questions will be important during that evaluation process.

    The grade earned for the project will be a team grade, that is, all team members will earn the same score for the project. However,the professor reserves the right to adjust individual team member's scores either upward or downward to support especially strong or weak performance and contributions to the group effort, as much as he can objectively determine. It is acknowledged that not all team members will bring the same skills to the group. It is each member's responsibility, however, to make a significant contribution in whatever way that best matches his or her abilities.

    Tips for a Successful Project

    It is extremely important to select an interesting problem with data that some group of people will care deeply about. I cannot stress enough how vital it is to start with interesting data. Find some topic that almost everyone cares about (e.g., baby names, feature films) or that some subset of people really care about (e.g., sports data, politics). Consider combining different data sets to produce a new composite data set of special interest. Such a fusion of data often creates a data set that people want to learn about. You may need to take a few weeks of the semester where you simply focus on data acquisition. That's OK. If you do not have your data nailed down by the poster session then you will be in deep trouble.


    Where do you get your data from? Be creative! You may have to scour the web and scrape some information. You may have to manually log and generate data tables. You may have to coalesce multiple different data sources. Part of your responsibility on the project is to come up with the data needed to drive your visualization. It is a crucial and vital initial step! Ideally, you should start with a problem or domain, find someone who knows more about it, and then look for data from there. Don't start your project simply by looking for any old dataset. Be more problem-driven than that. Below are some quick examples of places with nice data repositories. Also, consider organizations that run contests for developing visualizations. They can often serve as good sources of problems and data. Some examples are:

  • National Institute of Justice
  • Bank of England
  • Perceived vs. actual student interest, spatio-temporal analysis

    And finally, there are websites that can help you find data sets such as Awesome public datasets, Kaggle and Google's Dataset Search Tool.