AURORASAURUS: Citizen Science, Early Warning Systems and Space Weather

Andrea Tapia, Nicolas Lalone, Elizabeth MacDonald, Michelle Hall, Nathan Case, Matt Heavner

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

We have created Aurorasaurus, a website, a mobile application and a scientific tool that allows a community of users to better predict sightings of the aurora borealis. We focus on the aurora borealis as a rare and unpredictable event (as a proxy for a natural disaster), as it is in the middle latitudes, highly populated areas in North American and Europe. In the northern half of the continental United States the aurora may be visible once or twice per year. In the Southern half, perhaps only once every 20 years, especially during a solar maximum. We feel that the similarities between natural disaster occurrence and auroral occurrence can offer a chance for researchers to test elements of an Early Warning System. The years around 2014 are the latest solar maximum recurring on an eleven-year solar cycle. Now is the time when aurora is more likely over populated areas, and this is the first solar maximum with social media, an unprecedented opportunity to engage the public, the scientific community, and the media. Space weather scientists have only coarse means to predict where the aurora will occur.

Original languageEnglish (US)
Title of host publicationProceedings of the 2nd AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2014
EditorsJeffrey P. Bigham, David Parkes
PublisherAAAI press
Pages30-32
Number of pages3
ISBN (Electronic)9781577356820
StatePublished - Nov 5 2014
Event2nd AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2014 - Pittsburgh, United States
Duration: Nov 2 2014Nov 4 2014

Publication series

NameProceedings of the 2nd AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2014

Conference

Conference2nd AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2014
Country/TerritoryUnited States
CityPittsburgh
Period11/2/1411/4/14

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Human-Computer Interaction

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