Human Networks and Data Science

The Human Networks and Data Science (HNDS) program, administered by the National Science Foundation (NSF), is designed to support research that leverages data and network science methodologies to advance understanding of human behavior. Managed through NSF's Directorate for Social, Behavioral and Economic Sciences, and more specifically by the Divisions of Behavioral and Cognitive Sciences and Social and Economic Sciences, the program prioritizes data-intensive approaches to study human networks and their implications across social, economic, and behavioral contexts. The NSF, as a key federal agency, funds foundational research and education in science and engineering and operates with a mission to promote progress in these areas for national welfare. The HNDS program consists of two distinct tracks: Infrastructure (HNDS-I) and Core Research (HNDS-R). HNDS-I supports the creation of large-scale, user-friendly databases and analytic tools that facilitate advanced research in the social, behavioral, and economic sciences. These proposals must produce a finished product—either a database or analytical tool—that significantly broadens research capabilities in these fields. Products should be generalizable, impactful across multiple disciplines, and enable types of research not previously possible. HNDS-R, on the other hand, supports theory-driven research that applies network science and large-scale data analysis to answer core disciplinary questions. Projects in this track are expected to transform theoretical frameworks and generate new insights about human behavior, especially where these insights could result in societal benefits. Funding for the HNDS program totals approximately $8 million per year, with expected awards ranging from 5 to 25 across both tracks. A typical HNDS-I award ranges from $750,000 to $800,000, while HNDS-R awards typically range from $350,000 to $400,000. Projects can span from one to five years. While cost sharing is not required and voluntary matching is prohibited, proposals must align with the NSF’s policy frameworks and guidelines as specified in the Proposal & Award Policies & Procedures Guide (PAPPG). For HNDS-I proposals, two additional required supplementary documents must be submitted: a Technical Plan detailing implementation, staffing, and outreach, and a Sustainability Plan explaining how the product will be maintained and made accessible after the award period. Eligibility for this opportunity follows NSF-wide standards. Institutions of higher education, nonprofits, for-profit organizations, and certain government units are eligible, provided they are not unaffiliated individuals. Each organization can submit multiple proposals, though individuals can only serve as PI or co-PI on one HNDS-I proposal per year. There are no limits for HNDS-R proposals. While HNDS-R proposals are generally submitted to other core NSF SBE programs with HNDS-R listed as secondary, direct submission is allowed with prior written approval from the HNDS Program Officer. Application deadlines vary by track. HNDS-I proposals are due the second Thursday in January each year (e.g., January 10, 2025). Direct submissions to HNDS-R by permission only are due the first Thursday in August and February annually. Proposals using HNDS-R as a secondary track must follow the primary program’s deadlines. All proposals must be submitted via Research.gov or Grants.gov following the applicable submission guides. Applicants are encouraged to contact NSF program staff to discuss the alignment of their proposals, especially for HNDS-R submissions. The review process follows NSF’s standard merit review criteria, evaluating intellectual merit and broader impacts. Award notifications are typically issued within six months after submission. For more information or assistance, applicants can reach out to program contacts including Amy Criss and Nicholas Nagle. Detailed application instructions, including submission formatting, are available in the official solicitation and the PAPPG. The solicitation emphasizes ethical use of data and human subjects protection, aligning with federal research integrity policies.

Emphasize theoretical contribution, societal relevance, and ethical data use. Strong sustainability plans increase competitiveness.