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J Am Med Inform Assoc 2008;15:783-786 doi:10.1197/jamia.M2731
  • Original Investigation
  • Case Report

Development of Grid-like Applications for Public Health Using Web 2.0 Mashup Techniques

  1. Matthew Scotcha,
  2. Kevin Y Yipb,
  3. Kei-Hoi Cheunga,b,c
  1. aYale Center for Medical Informatics, Yale University, New Haven, CT
  2. bDepartment of Computer Science, Yale University, New Haven, CT
  3. cDepartment of Genetics, Yale University, New Haven, CT
  1. Correspondence: Matthew Scotch, Yale Center for Medical Informatics, Yale University, 300 George St., Suite 501, New Haven, CT USA 06511 (Email: matthew.scotch{at}yale.edu)
  • Received 25 January 2008
  • Accepted 22 June 2008

Abstract

Development of public health informatics applications often requires the integration of multiple data sources. This process can be challenging due to issues such as different file formats, schemas, naming systems, and having to scrape the content of web pages. A potential solution to these system development challenges is the use of Web 2.0 technologies. In general, Web 2.0 technologies are new internet services that encourage and value information sharing and collaboration among individuals. In this case report, we describe the development and use of Web 2.0 technologies including Yahoo! Pipes within a public health application that integrates animal, human, and temperature data to assess the risk of West Nile Virus (WNV) outbreaks.

The results of development and testing suggest that while Web 2.0 applications are reasonable environments for rapid prototyping, they are not mature enough for large-scale public health data applications. The application, in fact a “systems of systems,” often failed due to varied timeouts for application response across web sites and services, internal caching errors, and software added to web sites by administrators to manage the load on their servers. In spite of these concerns, the results of this study demonstrate the potential value of grid computing and Web 2.0 approaches in public health informatics.

Footnotes

  • This project is supported in part by The National Library of Medicine (NLM) Training Grant TI5 LM007056 to Matthew Scotch and National Institute of Neurological Disorders and Strokes (NINDS) grant U24 NS051869 to Kei Cheung.

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