Uploaded by luismauricio on Jan 18, 2010
Wiki: http://wiki.crisiscommons.org/index.php?title=.php&title=UN_Spider_Map/Di...
Project Leader:
Chris Nicholas
http://www.un-spider.org/
Project Team:
Kiran Vaka
Che Sharm
Christine DesMarais
Larry Sheradon
Luis Mauricio
James McBryan
Joe Cancilla
The Haiti earthquake is and will be one of the greatest tragedies of our time. Most of Haiti's infrastructure is down, leaving few ways for those in crisis on the ground to communicate their distress. As a result, people have gone to sites like Twitter and http://haiti.ushahidi.com, producing a long stream of 911 tweets that haven't been able to be followed up on.
In today's world of online social media, Haitians are crying out for help in different fashion, and it's important to translate those cries into action. For our CrisisCamp project, we are working to find the messages from Haitians on the ground and in need, and then aggregate them into something organized and actionable.
When we parse the Twitter and Ushahidi stream, the key detail we look for is location. If we can pinpoint the distress signal geospatially, then we can enter it into a process of evaluation and eventually, an assistive dispatch.
The Ushahidi data is fortunately already labeled with longitude and latitude, but for twitter, we were helped by one of the other teams at CrisisCamp. They put the stream through http://haititweets.makerlab.org/tweets.xml, a site that looks for semantic knowledge, such as a famous building, street name, or location nickname, and eventually is able to provide a longitude and latitude.
Once we have that, we provide a workflow process to efficiently lead to assistance. We have four types of users, ordered by increasing level of permissions. The first is an observer, who is the one who initially puts out the distress signal. We then have an authenticator, who reads over the message, authenticates it, and types it according to medical, construction, clearing, and security. We then have a qualifier, who is the one who produces a full report on all of the supplies and resources needed to respond fully to the distress. And then, now that all the data needed to send out a fully functional dispatch is organized and gathered, a dispatch can be sent with all of the necessary resources.
The beauty of this approach is that it allows for the few resources that exist on the ground to be used efficiently. For example, the map might show a cluster of medical needs in one neighborhood, meaning that an ambulance can be sent out knowing how many injured and ill people it should expect. And the workflow is flexible, in that if the number of medical dispatchers ever outnumbers the people doing the surveying and authentication, they have the permissions to act ahead of process, such as if there is a critical need for immediate help.
Hopefully by aggregating all of this data, we can provide a status and action report of what's happening in Haiti right now, and provide a means to efficiently and fully act upon it.
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