【實用教育app】Terrorism Data Tool|最夯免費app-綠色工廠好玩App

This is a RESTful mobile application. It retrieves information from a J2EE service in the form of JSON string. The application uses AChartEngine libraries to render graphs of the data. The data comes from http://www.start.umd.edu/start/ which provides an open source terror database. The organization that operates the website is the National Consortium for the Study of Terrorism and Responses to Terrorism which is a center for excellence of the U.S. Department of Homeland Security based at the University of Maryland. The database is apparently the most comprehensive database of terrorist attacks.

The data can be viewed and downloaded from http://www.start.umd.edu/start/ (not affiliated with this app). They make the database available as an Excel spreadsheet. For this app that data was imported into a MySQL database that the service uses.

This app provides two charts. One is for the top ten groups for a time period specified by the user of the application. A line chart is displayed with a data point for the number of attacks each year for each of the ten groups with the most attacks during that time.

The second chart is a pie chart. The pie chart also displays data for the top ten groups. The pie chart compares the total number of attacks by each group during the entire time period. Additionally, it displays two other groups. It also displays a group, "Unknown," and a group, "Bottom Groups." "Unknown" is the number of attacks by all of the groups that are not known. This listing always outnumbers every other group in every range of years. The second listing, "Bottom Groups," is the aggregate of 12th most active group to the nth most active group. Because "Unknown" is number one, the next ten in plus that one makes 11. Therefore, to get the aggregate number of attacks from all of the groups below "Unknown" and the next top ten groups, counting must begin at the twelfth entry and continue to the last entry.

The motivation for building this application was to allow users to draw objective inferences from data about a hot button issue. Hopefully, it can be a tool not only for personal reflection but also provide material for discussion.

This app was built for a research class in computer science at the University of Texas of the Permian Basin, Fall 2013. The group is Ira Cross, David Krause and Cyle Mansell. The adviser is Dr. Quan Yuan.