Collecting Analyzing and Vizualizing Data

August 4, 2016 / By Sharon Henry

Irvine, August 4, 2016 — In Uganda, in 1952, the virus known as Zika was first identified in humans. Until recently, the virus that produces flu-like symptoms, low-grade fever and headache was not considered a serious health risk.

However, in 2015, after a Zika outbreak in Brazil, the World Health Organization (WHO) declared the virus a public health emergency. Zika had been linked to microcephaly, a devastating birth defect in children born to women infected during their pregnancy. Babies born with the disorder often have an intellectual disability, poor motor function, poor speech, abnormal facial features, seizures, and dwarfism.

To date, more than 50 countries have confirmed Zika cases. The virus is expected to spread to the southern United States and infect up to 4 million people in the next year.

Surf IoT mentor, Chen Li

COLLECT, ANALYZE AND VISUALIZE 

It is the vast amount of Zika-related content being generated online that spurred Chen Li’s interest in developing a tool to capture and utilize data from social media. Li, a computer science professor at UC Irvine and SURF IoT mentor proposed researching a way to collect this information, analyze the data to extract valuable information and visualize the information.

Li’s team has collected 70 million tweets (15 per second), each contains at least one of 71 Zika-related keywords. They’re also gathering a rich set of data types from online news stories that include time, location, patient age and gender. The final step is to backup the data and allow uses to query and view live data in a visual format.

The result of having real-time, rich data, filtered from social media would be a big help to decision makers, Li said. The same tools could be used for myriad of very large data set, from the presidential election concerns of social media users to natural disaster reporting, as well myriad of commercial uses.  “We want to study challenges related to performing efficient search on large number of source code packages,” he added.

Zuozhi Wang, a computer science major and 2016 SURF IoT fellow, is also contributing to this project. A presentation discussing Wang’s research titled, “Developing a Code Search Tool to Help IoT Developers in Programming “ will be given, Aug. 25, at the SURF IoT Symposium held at Calit2.

SURF IoT, co-sponsored by UCI’s Undergraduate Research Opportunities Program (UROP) and Calit2, provides students with a unique learning experience. Each student has the guidance of a UCI faculty mentor, along with the opportunity to gain experience and advanced training in state-of-the-art facilities and techniques.