Building a Dynamic Explorer Tree to Investigate Behavioral Risk
Dr. Guenter Tusch, firstname.lastname@example.org
In today’s world, especially in health care, good data is the key to good decision making. The massive collection of data on many subjects continues daily and more of this data is becoming freely available to the public to be explored. Yet even if this data is loaded into a relational database, it may not be accessible to researchers or decision makers who may not be experienced in writing SQL. Users of varying experience levels need tools that can help them visualize data and make its information more accessible.
The purpose of this project was to develop a web based application that can enable users to explore data already stored in a database, using an interface familiar to many computer users. My approach was to represent database querying, through the use of a tree structure similar to that used in file explorers, such as in the Microsoft Windows operating system. The content displayed in the tree interface is displayed dynamically based on which nodes in the tree are opened. The developed solution was built using Microsoft Silverlight, C#, ASP.NET, LINQ to SQL, and SQL Server.
The Centers for Disease Control and Prevention’s (CDC) Behavioral Risk Factor Surveillance System (BRFSS) was used as an example dataset. The BRFSS is state based and the world’s largest, on-going telephone health survey system, tracking health conditions and risk behaviors in the United States yearly since 1984. States use BRFSS data for a multitude of purposes, e.g., to identify emerging health problems and establish and track health objectives, or support health-related legislative efforts. For many states, this is the only data source on health-related behaviors. The BRFSS 2009 data contains 432,607 responses and 400 questions. The size of this dataset makes it both a challenge to study, yet full of interesting querying possibilities.
The application is accessible through this website: http://capstone.arivium.com/.
Bund, James W., "Building a Dynamic Explorer Tree to Investigate Behavioral Risk" (2010). Technical Library. Paper 140.
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