Latest News and Events

The SAMSI-FODAVA Workshop on Interactive Visualization and Analysis of Massive Data will be held on December 10-12, 2012.
Posted: October 02, 2012
The FODAVA Annual Meeting will immediately follow (Dec 12-13) the SAMSI/FODAVA joint workshop at the same location.
Posted: September 05, 2012
Many of the modern data sets such as text and image data can be represented in high-dimensional vector spaces and have benefited from computational methods that utilize advanced techniques from num
Posted: June 30, 2012

About FODAVA

Enormous amounts of data are being generated every day in health care, computational biology, homeland security, commerce, and many other areas. Analyzing these massive and complex data sets is essential to achieve new discoveries, but extremely difficult. An emerging research field known as data and visual analytics is concerned with synthesizing information and deriving insight from massive, dynamic, ambiguous and possibly conflicting digital data for increased understanding and effective decision making.

The Foundations on Data Analysis and Visual Analytics (FODAVA) research initiative is dedicated to both defining the foundations of the data and visual analytics fields and advancing the state-of-the-art. Established in 2008, the FODAVA initiative is a collaborative effort funded jointly by the National Science Foundation (NSF) and the Department of Homeland Security (DHS).

The Georgia Institute of Technology, as the FODAVA-Lead institution will lead and coordinate this new initiative. It will perform foundational research in massive data analysis and visual analytics. It will investigate ways to improve the visual analytics of massive data sets through advances in areas such as machine learning, numeric and geometric computing, optimization, computational statistics, and information visualization. It will work to establish FODAVA as a distinct research field and build a community of researchers that will collaborate through research workshops and conferences, industry engagement and technology transfer.

Developing new and improved mathematical and computational methodologies will further enable systems developers, intelligence analysts, biologists and health care workers to implement new methods to ‘detect the expected and discover the unexpected’ among massive data sets.

Read more about FODAVA