Visualizing and Understanding Trends in Data
It is estimated that in 2014–2015 alone, the world produced a volume of data nine times larger than all other data previously generated. Given the recent and rapid advances in data production, storage and sharing, we are experiencing a cultural shift toward a more analytic, data-driven society.
Despite the many benefits of such abundant data, its sheer quantity is starting to overwhelm our capacity to interpret and make meaningful use of it. This gap could create obstacles in decision-making and challenges for consumers of casual information.
Various computational solutions have been proposed to help cope with this data deluge, including some promising approaches from machine learning and visualization. As Canada Research Chair in Data Visualization, Dr. Fernando Paulovich is exploring our ability to take advantage of the “intelligence” offered by machine learning. He is using interactions with visual representations to develop more robust and reliable tools and techniques to address the current challenges in big data.
Paulovich’s goal is to create technologies to analyze time-dependent data to allow users to understand or predict how different phenomena will evolve. He and his research team are exploring different application domains, from sports analysis to environmental monitoring. Ultimately, their work will change and improve our daily routines, helping us understand and make the most of this "brave new information world."