Monday, July 7, 2014

2014-07-07: InfoVis Fall 2012 Class Projects


(Note: This is continuing a series of posts about visualizations created either by students in our research group or in our classes.)

I've been teaching the graduate Information Visualization course since Fall 2011.  In this series of posts, I'm highlighting a few of the projects from each course offering.  (Previous post: Fall 2011)

The Fall 2012 projects were based on the 2012 ODU Infographics Contest. Participants were tasked with visualizing the history and trajectory of work done in the area of quantum sensing. (All class projects are listed in my InfoVis Gallery.)

Top Quantum Sensing Trends
Created by Wayne Stilwell


This project (currently available at https://ws-dl.cs.odu.edu/vis/quantum-stilwell/) is a visualization for displaying the history and trajectory of quantum sensing. History is shown as a year-by-year slideshow. The most publicized quantum sensing areas for the selected year are displayed. Clicking on a topic shows the number of publications on that subject over time compared to the most popular topic (gray line). This allows users to see when a subject started to rise in popularity and at what point in time (if any) it started to decline. The visualization also shows which research groups have the most publications for the selected subject. When a new year is chosen, animation is used to show which topics increased in popularity and which decreased. The final slide in the visualization is a projection for the year 2025 to show where quantum sensing is headed in the future.  This project won the overall competition.

The video below provides a demo of the tool.



BibTeX Corpus Visualizer
Created by Mat Kelly


One method to find trends in any industry is to examine the publications related to that industry. Given a set of publications, one should be able to extrapolate trends based on solely on the publications' metadata, e.g., title, keywords, abstract. For one to analyze text data to determine trends is daunting, so another method should be used that analyzes this data and presents it in a way that can be easily consumed by a casual user. This casual user should be be able to achieve the goal of identifying trends in the respective industry. This project (currently available at https://ws-dl.cs.odu.edu/vis/quantum-kelly/index.php) is a visualization that examines a small corpus consisting of metadata (in BibTeX format) about a collection of articles related to Quantum Sensing. The interface allows a user to explore this data and conclude many attributes of the data set and industry, including finding trends.  This project was built using the jQuery and D3.js libraries.

The video below provides a demo of the tool. 


Mat is one of our PhD students and has done other visualization work (described in his IEEE VIS 2013 trip report).

-Michele

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