Welcome to Bungee View

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Bungee View is designed to support non-technical users in gaining an understanding of an image collection as a whole, and in finding patterns in their meta-data, while they search and browse. Since this is a research project, your usage will be recorded to help improve Bungee View. We will use your IP address to track your repeat visits, but will not attempt to identify you as a person. Feedback is welcome at (Mark Derthick).

For a brief tour, watch this two minute video as an avi or a worse quality mov (the DivX codec should work for either).

Run Bungee View

  1. Click to as a Java Web Start application in a new window.*
  2. Once it starts, click on any underlined text, or on any image or bar.
  3. For more information, use the Help menu.

* If your browser doesn't know how to open this link, it means you need to install Java 1.5 or later, which includes the Java Web Start plug-in.

* If you are using Safari, it may download the Java Web Start file (bungee.jnlp or similar) without opening it. Click on Safari's down arrow icon to show recent downloads, and click on the file to open.

* If you have Java 1.7 or later, you may get a pop-up warning that this application is unsigned. Click "More Information" on the popup to see that it is not really very dangerous.
  Dang. With Java 1.7.51 the popup just says the application is blocked by security settings. You have to add the URL "http://cityscape.inf.cs.cmu.edu/bungee/" to the Java Control Panel exception list. Go to the Control Panel, search for "Java", open its Security tab, and click "Edit Site List."

Data-Mining with Bungee View

Bungee View enhances browsing image collections with two overview visualizations that replace Tag Clouds:

 

 

 

 

 

 

Tag Cloud

    Quickly summarizes a set of documents

    Up to ~30 characteristic tags

 

Top Tags

    Quickly summarizes a set of documents

    Up to ~30 characteristic and uncharacteristic tags

 

Tag Wall

    More quantitative and detailed summaries, and also supports searching and filtering

    Summarizes: rectangle width shows that more than half of the works in the collection are from the 20th century

    Compares: rectangle height upward and green color shows that the current result set includes an even higher percentage of 20th century works than the collection as a whole.

    Up to ~1000 tags (and even more when you zoom or filter)

    Organizes tags by category, like Date and Format

    Systematic and consistent tag layout creates stable maps of the collection

    Shows what is not present

    With thousands of organized and sorted tags to filter on, you may not even need the text search box. This is important in image collections with little text, since the keywords you have in mind may not occur at all.

 

Motivation

Web search engines have attracted widespread demand for information retrieval from unstructured documents. The number of structured and semi-structured documents available on the Web is also huge, and collections of these are more amenable to data mining. Yet there has been no similar explosion of interest in this kind of exploration. Finding patterns in databases of political contributions, environmental data, or hospital and school performance would surely interest many citizens. The main research question for this project is how to support such exploration for users with little or no training in statistics or programming. In contrast to other data-mining systems, Bungee View focuses on learnability, responsiveness, robustness, and providing a satisfying user experience.

Have a collection?

Let me help you make it available through Bungee View! The project site contains the source code and documentation for Bungee View Administrators and Developers.

Bungee View version 11/2007, Copyright (C) 2007 Mark Derthick
Bungee View comes with ABSOLUTELY NO WARRANTY; This is free software, and you are welcome to redistribute it under certain conditions; Choose "About Bungee View" on the Help menu for details.


Mark Derthick ()
Last update: 17 April 2014