Epidemiological Data Visualization and Web 2.0 - The U.S. Cause of Death Project

Document Type


Lead Author Type

MBI Masters Student


Dr. Guenter Tusch, tuschg@gvsu.edu

Embargo Period



Since Tim Berners-Lee’s article “The Semantic Web - A new form of Web content that is meaningful to computers will unleash a revolution of new possibilities” appeared in 2001 in the Scientific American, an Internet revolution took place. The Semantic Web effort itself does not provide computer application programs - it rather provides standards to interlink those computer applications. Web 2.0 refers to a class of Web-based computer applications to share certain design patterns including, for instance, wikis, personal Web pages and blogs, and to create a structure for and attach “knowledge” to content. Many Web 2.0-style application programs and companies now exist, including Flickr, Wikipedia, YouTube, Google, MySpace, or Facebook. Due to the wide spread acceptance of the Web 2.0-style incorporating its ideals into the visualization of Medical Informatics data follows a logical progression. Google and Yahoo recently developed Web Libraries that provide open source sets of tools that allow web developers to create and maintain complex JavaScript front-end applications. They especially provide rich visualization features that can be used to visualize time trends in epidemiological data. This project uses geo-spatial visualization techniques, courtesy of the Google Code Library, on a US cause of death dataset. In epidemiology, large data sets are collected and indexed by geo-spatial location. Discovering unique patterns through visualization is an important way of gaining insight about such data. Epidemiological data in the US are in general very complex involving different geographical regions, medical features, and time trends. The goal of this project is to visualize cause of death data in the United States using a variety of variables. The data set utilized for the project is the Web-based Injury Statistics Query and Reporting System sponsored by the Centers for Disease Control. Currently, the data set contains information regarding every death in the United States from 1981 to 2006. The project aggregates this information across predetermined age groups, states, and time. Users of the project are able to compare death information across all three variables. As a result, significant advancements have been made in the overall accessibility and usability of the data regardless of the technical abilities of the end user. This project is an example of how information technology and visualization of epidemiological data can be made available to any user of the Internet. Such tools may work to change the understanding of the general public about epidemiological findings and can also be used in a doctor-patient relationship towards joint decision-making based on health risk management.

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