Foundations of Data and Visual Analytics  (FODAVA)

PROGRAM GUIDELINES

Solicitation  07-583

SYNOPSIS

Those involved with science, engineering, commerce, health, and national security all increasingly face the challenge of synthesizing information and deriving insight from massive, dynamic, ambiguous and possibly conflicting digital data. The goal of collecting and examining these data is not to merely acquire information, but to derive increased understanding from it and to facilitate effective decision-making. To capitalize on the opportunities provided by these data sets, a new, interdisciplinary field of science is emerging called Data and Visual Analytics, which is defined as the science of analytical reasoning facilitated by interactive visual interfaces. Data and Visual Analytics requires interdisciplinary science, going beyond traditional scientific and information visualization to include statistics, mathematics, knowledge representation, management and discovery technologies, cognitive and perceptual sciences, decision sciences, and more. This solicitation is concerned only with a subset of the overall problem, namely the creation of the mathematical and computational sciences foundations required to transform data in ways that permit visual-based understanding.

To facilitate visual-based data exploration, it is necessary to discover new algorithms that will represent and transform all types of digital data into mathematical formulations and computational models that will subsequently enable efficient, effective visualization and analytic reasoning techniques.

With this solicitation, the National Science Foundation (NSF) and the Department of Homeland Security (DHS) invite research proposals that capitalize on knowledge and expertise in the fields of mathematics, computational science, and intelligent systems to produce new data representations and transformations to enable data stakeholders to detect the expected and discover the unexpected in massive data sets. New mathematical and computational algorithms and techniques are sought that will fundamentally improve our ability to transform large, often streaming data sets into representations that better support visualization and analytic reasoning.

In order to provide a cohesive structure for advancing the science of Data and Visual Analytics, two types of proposals are sought:

•   FODAVA-Lead proposals will be submitted by research teams where all team members belong to a single academic institution willing to assume a leadership and coordination role.  FODAVA-Lead proposals will compete for a single award with the successful institution expected to play a key role in the development of FODAVA. In addition to forming the lead scientific research team, the FODAVA-Lead organization will be responsible for performing a variety of functions as defined in Section II of this solicitation in order to assure that results are disseminated to the FODAVA community, that effective liaison between FODAVA researchers and the DHS National Visualization and Analytics Center (NVAC) takes place, that testbed data sets are developed and disseminated, and that the mathematics and computer science research communities become increasingly aware of the need for FODAVA-related research

•   FODAVA-Partner proposals will be submissions for two-to-three year research grants. Recipients will perform fundamental research but will also actively participate with the FODAVA-Lead institute in developing FODAVA as a field.

Awards made are expected to develop the mathematics and computational science required to transform data in ways that will better enable the visual-based analysis of massive data sets. The solicitation's goal is to develop new data reduction and transformation algorithms that will be applicable across broad application areas, laying the scientific base for systems of the future. Proposals should focus on fundamental research advances that will be widely applicable across scientific, engineering, commercial, and governmental domains that utilize visualization and analytics to gain insight and derive knowledge from massive data sets.  FODAVA is focused on highly innovative, transformational research that offers the potential to fundamentally change data transformation algorithms. Proposals to extend ongoing research thrusts should be directed elsewhere.

THIS PROGRAM IS PART OF

Additional Funding Opportunities for the CCF Community

Additional Funding Opportunities for the IIS Community

Special Research Programs

Abstracts of Recent Awards Made Through This Program