Data in Action: Informing Disaster Relief
When disaster strikes, the time it takes to get rescue workers and supplies to an affected area can determine the fate of countless lives.
With the frequency and severity of global natural disasters, such as earthquakes and typhoons, on the rise, disaster relief teams are relying more and more heavily on data and data scientists to help reduce response times and create hyper-targeted and increasingly efficient action plans.
Crisis mapping is a crucial component of the process, which essentially allows relief organizations to view and classify the varying types and levels of damage incurred across an entire disaster zone.
Recently, in Jakarta, a data-driven disaster response tool was developed to aid residents and relief teams during monsoon season - an annual period of extreme weather and widespread flooding throughout the city. The tool pulls data from tweets to create a live crisis map, helping to pinpoint areas of concern and mitigate further damage or loss of life.
Developed by the SMART Infrastructure Facility, in collaboration with the city of Jakarta, and Twitter Inc., “this geosocial intelligence framework allows data to be collected and disseminated by residents through their location-enabled mobile devices to map flooding and water infrastructure in real time,” according to PetaJakarta.org, the group's official website.
Harnessing the power of Jakarta’s existing and expansive Twitter network, the organization created a simple, 3-step process whereby users can geo-tag their location, post a photo of the flood from their point of view, and send a report with the hashtag #banjir to @petajkt. Machine learning algorithms are applied to the tweets to help organize and categorize the data into actionable information in the form of a live, open-sourced crisis map.
This data-driven platform not only makes it possible for residents to see which areas are safe and which ones should be avoided during a flood, it also enables the millions of Twitter users in Jakarta to easily contribute to disaster relief efforts from their mobile devices, while providing response teams with an effective and up-to-the-minute tool for accessing damage and planning swift, decisive action.
It’s a clear example of the positive impact that data science can have on real world outcomes. In this case, turning data into knowledge is not only creating efficiencies, it’s helping to save lives.