From CS 725/825 Spring 2015

CS725-S15: Semester Project

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Report Due: Mon, May 4, 2015 by 8:00am - updated!
Presentation/Demo: Tue, Apr 28, 2015 during class time


The idea of the project is to take the knowledge and background that you are learning this semester about Information 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" or "analysts" 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.


Students should work on a project in teams of 2 people. (Arguments will be entertained for a single person project.) Expectations will be adjusted according to group size.

Teams and Projects

1) Hassan and Alexander - My Twitter Neighborhoods - website
2a) Wessam - Annotation Analyzer - website, demo
2b) Mohammed - Visualizing Annotations in - demo
3) Apeksha and Raghav - Economic Impact of Coastal Sea Level Rise and Flooding - website
4) Avinash and Prasanna - ODU HR Salary Data for the Mace and Crown - website
5) Kayla and Swaraj - DoD Contracting in HR - flow nationwide - website
6) Shawn and Valentina - DoD Contracting in HR - focus on HR - project blog, demo
7) Srividya and Ilho - Exploring Crime Rate in the US using Leap Motion - website, demo
8) Teresa - Coastal Ocean Surface Current Visualization - website

Important Milestones

Project Proposal Presentation

Project Website

The website should contain the following info:

What-why-how framework table: There are some nice examples of how to start framing this in Chapter 15. For each of the visualization tools in that chapter, there's a table that describes things like "what: data", "what: derived", "why: tasks", "how: encode". I would encourage you to start putting this table together as soon as possible. The "what' and "why" tasks should be driving how you develop the "how". Remember that the "why: tasks" need to be general, as described in Chapter 3.

You may also want to include a list of domain-specific questions that you plan your visualization to allow users to explore.

And at the end of the semester, this webpage should also have a link to your live project.



See Process and Pitfalls in Writing Information Visualization Research Papers by Tamara Munzner


I will evaluate the overall quality of your project, including all milestones and components. The following questions will be important during that evaluation process:

Grading Sheet

Project Ideas

Not to intimidate you (well, maybe a little), here are the final class projects from Jeffery Heer's class at Univ of Washington.

History Mapping / Holden

Project description (pdf), example design/model (pdf)


Contact: Dr. Bob Holden (rholden at odu dot edu)

Hampton Roads Planning District Commission / Clary

Description of projects (pdf)

Data Sources:

Contact: James Clary (jclary at hrpdcva dot gov)

Mace & Crown Data Vis

ODU's student newspaper, The Mace & Crown is interested in producing ODU-specific data visualizations for either online or print. They have access to data sources around campus (e.g., Alumni Center, Institutional Research) and would be interested in discussing potential items to investigate.

Contact: Jugal Patel (jpate016 at odu dot edu)

MARI/CCSLRI - Impacts of Sea Level Rise

Create a visualization (or set of visualizations) that combine flooding data with economic data. Potential visualizations include:

Data sources:

I have many more data sources and links that I can share with interested groups.

Drug Manufacturers and Doctors



Expand the AutoSPLOM tool ( to provide more views of the data. For instance, allow user to click on one of the scatterplots to reveal a bar chart of the data in that scatterplot. Make other interface and visualization enhancements as needed.

FluNet / SandyVis extensions

1) Expand the SandyVis visualization ( For instance, add nuisance flooding values to the JSON data and graphs, only highlight stations where the water values have crossed the nuisance level.

2) Expand the WorldVis visualization (l For instance, make the code extendable to any type of world data, add graphs at the bottom.

Both of these would require additional development than what is described here. The suggestions are just to get you started.

Based on project guidelines from John Stasko, Georgia Tech

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