The BIGDATA program seeks novel approaches in computer science, statistics, computational science, and mathematics, along with innovative applications in domain science, including social and behavioral sciences, education, biology, the physical sciences, and engineering that lead towards the further

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development of the interdisciplinary field of data science.

The solicitation invites two categories of proposals:

• Foundations (F):
  those developing or studying fundamental theories, techniques, methodologies, and technologies of broad applicability to big data problems, motivated by specific data challenges and requirements; and
• Innovative Applications (IA):
  those engaged in translational activities that employ new big data techniques, methodologies, and technologies to address and solve problems in specific application domains.
  
  Projects in this category must be collaborative, involving researchers from domain disciplines and one or more methodological disciplines, e.g., computer science, statistics, mathematics, simulation and modeling, etc.

Proposals in both categories must include a clear description of the big data aspect(s) that have motivated the proposed approach(es), for example:
the scalability of methods with increasing data volumes, rates, heterogeneity; or data quality and data bias; etc.

Innovative Applications proposals must provide clear examples of the impacts of the big data techniques, technologies and/or methodologies on (a) specific domain application(s).

Proposals in all areas of sciences and engineering covered by participating NSF directorates and partnering agencies [the Office of Financial Research (OFR)], are welcome.

Before preparing a proposal in response to this BIGDATA solicitation, applicants are strongly urged to review other related programs and solicitations and contact the respective NSF program officers listed in them should those solicitations be more appropriate.

In particular:

• For the development of robust and shared data-centric cyberinfrastructure capabilities, applicants should consider the Data Infrastructure Building Blocks (DIBBs) program, https://www.nsf.gov/funding/pgm_summ.jsp?pims_id=504776;
• For computational and data science research not specifically addressing big data issues, applicants should consider the Computational and Data Enabled Science and Engineering (CDS&E) program, http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=504813;
• For work that is focused more on scaling of software, rather than data-related issues, applicants should consider the Scalable Parallelism in the Extreme (SPX) program, https://www.nsf.gov/funding/pgm_summ.jsp?pims_id=505348;
• Proposals that are specific to the geosciences, and respond to the community needs and requirements expressed by the geosciences community, should consider the NSF EarthCube program for Developing a Community-Driven Data and Knowledge Environment for the Geosciences, https://www.nsf.gov/geo/earthcube/;
• Proposals that focus on research in mathematics or statistics that is not tied to a specific big data problem should be submitted to the appropriate program within the MPS Division of Mathematical Sciences (DMS); see a list of DMS programs at https://www.nsf.gov/funding/programs.jsp?org=DMS; and
• Proposals that focus on research in the computer and information sciences not tied to a specific big data problem should be submitted to the appropriate CISE core program:
  
  • Computer and Network Systems (CNS) Core Programs:
    https://nsf.gov/publications/pub_summ.jsp?WT.z_pims_id=12765&ods_key=nsf16579;
  • Computing and Communication Foundations (CCF) Core Programs:
    https://nsf.gov/publications/pub_summ.jsp?WT.z_pims_id=503220&ods_key=nsf16578; and
  • Information and Intelligent Systems (IIS) Core Programs:https://nsf.gov/publications/pub_summ.jsp?WT.z_pims_id=13707&ods_key=nsf1658 1.