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A Web Based Tool For the Detection and Analysis of Avian Influenza Outbreaks From Internet News Sources


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Paper presented at AutoCarto 2008 - Shepherdstown WV

Paper presented at AutoCarto 2008 - Shepherdstown WV

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  • 1. A Web Based Tool For the Detection and Analysis of Avian Influenza Outbreaks From Internet News Sources Ian Turton and Andrew Murdoch GeoVISTA Center Penn State University
  • 2. Flight?
  • 3. Summary
    • Who we are?
    • Why we did it?
    • What is Avian Flu?
    • What we did?
    • How we did it?
    • Did it work?
    • What will we do next?
  • 4. Who we are?
    • Ian
      • Senior Research Associate in GeoVISTA Center
      • E-Education Fellow in Dutton E-Education Institute.
    • Andrew
      • MGIS Student (graduated in Summer 2008)
      • GIS Developer at ArcBridge Consulting and Training
  • 5. What we did?
    • Andrew needed a project for Ian’s course on web mapping, and later for his capstone project (like a dissertation).
    • Ian had an interest in extracting geographic information from unstructured text.
    • Picked the spread of Avian Influenza and how to map it automatically from news reports.
  • 6. What is Avian Flu?
    • Avian flu or Bird flu is a virus
    • Most scary strain is H5N1 but there are many others.
    • ~60% death rate in humans.
    • Currently no (or very limited) human to human transmission.
    Picture by Quiplash ! CCbyA
  • 7. What we did?
    • Designed and built a system to automatically read internet news articles and map them for us so we could gain a better understanding of how avian flu is spreading on a day to day basis.
    • Set it running to see how it did
    • Tweaked it a bit as we saw how it worked
  • 8. How we did it?
    • Data sources
    • Data processing tools
    • GeoCoding tools
    • Web Mapping tools
      • Server
      • Client
  • 9. Data Sources
    • Official Avian Flu sites
      • WHO
      • PROMED
    • Internet News sites
      • Google News
      • Feedburner
    • Collected as RSS feeds
  • 10. Why does this work?
    • Media panic/interest leads to widespread reporting of any avian flu story.
    • Use of medical blogs like PROMED also helps overcome government restrictions on reporting.
    Pictures: ianstacey, quiplash, Incessantflux CCbyA
  • 11. What is RSS?
    • Really Simple Syndication
    • RDF Site Summary
    • A standardized XML file for passing information about web log (blog) updates.
    • You normally view RSS feeds in a feed reader
    • We wrote programs to read for us.
  • 12. Finding the geography
    • Step one extract the place names, named entity extraction
      • Custom tools
      • Reuters’ Calais system
      • MetaCarta
    • GeoCode the places, disambiguate London, Washington etc
      • Custom tools
      • MetaCarta
  • 13. Well that can’t be too hard?
  • 14. Web Mapping Server
    • Open Web Mapping Standards from the OGC (allows others to use our data).
    • Open Source tools (we’re a poor university).
    • Store the data points and news text in PostGIS (free spatial database).
    • GeoServer to serve maps from the DB to web (and desktop) clients.
  • 15. Mapping Client
    • Remember our end users are epidemiologists not GIS users so stick with a web browser as client.
    • OpenLayers (
      • JavaScript library that implements the OGC WMS and WFS standards our server uses.
      • Allows rapid construction of an interactive web map by relative novice developers.
      • The finished map looks a lot like a Google map so users can use it easily.
  • 16. The Map Choice of background layers Choice of feeds
  • 17. Zoom and Pan
  • 18. Time Line
    • We are also interested in change over time.
    • Added SIMILE Timeline from MIT
      • JavaScript tool allows user to scroll through time or date stamped information
  • 19. Link to external pages
  • 20. Query the map
  • 21. Did it work?
    • Yes,
    • Well mostly,
    • Well some of the time!
    • We can take news feeds, geocode them and draw maps in a web browser.
  • 22. What didn’t work?
    • News sources and even medical feeds contain too many items that are about avian flu in a general sense but not actually about an outbreak.
      • Conferences about avian flu
      • Vaccine news
      • Reports of other influenza outbreaks
      • Reports of other infectious diseases (“unlike avian flu…”
  • 23. What will we do next?
    • Improved selection of RSS items
    • Bayesian classifier
      • Train on a selection of “good” and “bad” items
      • Allow user to rate articles
    • Non-negative matrix factorization
      • Clusters similar items based on word usage
      • Help overcome repeated reports
  • 24. What will we do next?
    • Continue to improve the GeoCoder
      • Better disambiguation algorithms.
      • Allow user to rate the accuracy of locations found in reports.
    • Improve User Interface
      • Better selection of points of interest using timeline
      • Replace SIMILE with custom time bar
  • 25. Conclusions
    • It is possible to construct an online automated system that can read news articles from professional and general news feeds and map them in a way that allows experts and members of the public to track the spread of avian flu outbreaks.
    • There is still much work that can be carried out to improve this work.