Beyond the direct access that you get to celebrities, politicians and athletes you admire, Twitter can be a powerful tool to connect with a large, like-minded audience. Data scientists like Twitter because of its capability to disseminate information at such a high rate of speed. Gathering this data can make a huge difference in disaster situations while also posing quite a few complications. Quite often, organizations do not have the capability to handle the 3 V’s of Big Data: volume, velocity and variety.

Volume of data is rather self-explanatory, referring to the quantity of data, velocity refers to the speed at which data is created, and variety refers to the different types of data that is collected (phone, e-mail, GPS, social media etc). Variety can therefore represent both public and private sources. In a crisis situation, privacy concerns can be overlooked so it is important that those handling the data do so ethically. One way to do so is to improve the filters that handle the data, whether that is with human computing or machine computing. The Red Cross, for example, has a Digital Operations Center that manually reads approximately 5,000 tweets a day. During a disaster however, there is often a flood of tweets and other information. After a category 5 tornado hit Moore, Oklahoma for example, over 3 millions tweets regarding the disaster were published in 48 hours. That is incredible velocity and volume, showing the power of social media data in a real-time disaster situation.

Utilizing the 3 V’s of big data efficiently is essential to the mission statement of Operation Dragon Fire. In particular, collection of social media data will be crucial for the success of the platform. Along with a wide user base, the Operation Dragon Fire program will be able to collect a large volume and variety of data at a high velocity. It is this data that will be used to improve the effectiveness of disaster response, relief and recovery.