Michael Vogelius, Nandini Kannan, and Xiaoming Huo, NSF Division of Mathematical Sciences
The Big Data phenomenon has emerged as a result of the vast amounts of data becoming available across science, business, and government. Realizing the potential of Big Data will require fundamentally new techniques and technologies to handle the complexity, size, or rate of these data. Principled, innovative approaches are needed to address the challenges associated with the management, modeling, and analysis of such unprecedented amounts of data, including automation of aspects of the data-enabled discovery processes; development of new computational, mathematical, and statistical methods for data analysis; and creation of novel visualization techniques for drawing insights from data.
The National Science Foundation just released a revised version of the solicitation “Critical Techniques and Technologies for Advancing Foundations and Applications of Big Data Science & Engineering (BIGDATA).” This crosscutting initiative includes participation of all the NSF directorates, including the Directorate of Mathematical and Physical Sciences (MPS). The list of cognizant program officers includes Xiaoming Huo and Nandini Kannan from the Division of Mathematical Sciences (DMS).
This solicitation should be of particular interest to the statistics community, with its emphasis on both fundamental theoretical and methodological issues related to Big Data and the development of tools and techniques for the analysis of Big Data from different application domains.
The BIGDATA program invites proposals in two categories:
Foundations (F): those that focus on the development of novel techniques, or novel theoretical analysis (including statistics and probability) or experimental evaluation of techniques, that are broadly applicable.
Innovative Applications (IA): those that focus on the development of innovative techniques, methodologies, and technologies for specific application areas or innovative adaptations of existing techniques, methodologies, and technologies to new application areas.
Potential research areas and challenges in Big Data may include the following:
- Reproducibility, replicability, and uncertainty quantification
- Data confidentiality, privacy, and security issues as they relate to Big Data
- Generating hypotheses, explanations, and models from data
- Prioritizing, testing, scoring, and validating hypotheses
- Interactive data visualization techniques
- Scalable machine learning, statistical inference, and data mining
- Eliciting causal relations from observations and experiments
- Addressing foundational mathematical and statistical principles at the core of the new BIGDATA technologies
The program page provides a link to the solicitation, the list of program officers representing the different directorates, and a link to recent awards made through this program. Please read the solicitation for information about proposal preparation and submission, review criteria, and required supplementary documentation. The deadline for submission of BIGDATA proposals is May 20.
If you are interested in serving as a reviewer for proposals or would like additional information, contact Xiaoming Huo at xhuo@nsf.gov or Nandini Kannan at nakannan@nsf.gov.
Editor’s Note: Michael Vogelius is division director of the Division of Mathematical Sciences, and Xiaoming Huo and Nandini Kannan are program directors there.
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