Human Networks and Data Science | 22 505

Frequently Asked Questions (FAQs): NSF Human Networks and Data Science (HNDS) Program

What is the NSF Human Networks and Data Science (HNDS) program?

The National Science Foundation (NSF) Human Networks and Data Science (HNDS) program is a research funding opportunity focused on improving scientific understanding of human behavior by combining network science with modern data science. It emphasizes using dynamic, distributed, and highly diverse data sources to generate data-rich insights about human networks, with the broader aim of supporting better outcomes related to health, prosperity, and security.

What kinds of questions or topics is HNDS designed to support?

HNDS is designed to support research that studies individuals and groups through the lens of human networks using modern, data-intensive approaches. The program highlights that new kinds of questions can be studied because researchers increasingly have access to data that change over time, come from multiple systems, and include diverse formats or levels of detail.

What are the two HNDS tracks?

HNDS is organized into two complementary tracks: (1) Human Networks and Data Science - Infrastructure (HNDS-I) and (2) Human Networks and Data Science - Core Research (HNDS-R). The infrastructure track focuses on building community resources (data and tools), while the core research track focuses on theory-advancing research within a core Social, Behavioral, and Economic (SBE) discipline using network and data science approaches.

What is HNDS-I (Infrastructure) intended to fund?

HNDS-I supports projects that build underlying resources the broader research community can use. Proposals are expected to create large-scale, next-generation data resources and/or analytic techniques that are user-friendly and ready for others to use, such as curated databases, usable data platforms, or validated analytic tools and methods.

What does NSF mean by a "finished product" in HNDS-I?

For HNDS-I, the expectation is that the award period results in something concrete and accessible to the community. Examples mentioned include a curated database, a usable data platform, or validated analytic tools and methods that enable new kinds of data-intensive work in the SBE sciences.

How broad should the impact be for an HNDS-I project?

A strong HNDS-I project is expected to have significant impact beyond a single local use case. It should not be just a local dataset or a one-off tool; it should be designed to enable research across multiple fields or at least across a broad disciplinary area by making previously difficult or impossible research feasible.

What is HNDS-R (Core Research) intended to fund?

HNDS-R funds research projects that directly advance theory within a core SBE discipline by applying data science and network science approaches. The aim is for supported work to produce findings that enhance, expand, or transform theories and methods in the SBE sciences.

What types of data are HNDS-R proposals expected to use?

HNDS-R proposals are expected to use large and complex datasets, including data that span multiple spatial and temporal scales. The program description also notes that projects may draw on multi-scale or multi-level network data, such as networks that connect people to groups, organizations, or places.

Can HNDS-R projects combine qualitative and quantitative approaches?

Yes. HNDS-R proposals may combine qualitative and quantitative approaches when using both strengthens inference or interpretation.

What kinds of analytic approaches are relevant to HNDS-R?

HNDS-R highlights the use of network science and data science approaches, including advanced network analytic techniques, particularly when applied to complex and multi-scale network data tied to human behavior.

Does HNDS-R encourage use of existing NSF resources?

Yes. HNDS-R particularly encourages researchers to build on existing NSF-supported data resources, networks, centers, and other infrastructure, including resources created through the HNDS infrastructure track.

How does HNDS-I relate to RIDIR?

The program description notes that HNDS-I builds on what was formerly associated with RIDIR efforts, indicating continuity with prior NSF activities focused on developing research infrastructure and data resources.

What is the opportunity number for this NSF funding program?

The opportunity number listed is 22-505.

What is the CFDA number and category for this opportunity?

The program is described as an NSF discretionary grant program in the Science and Technology and other Research and Development category, with CFDA 47.075.

Who is eligible to apply?

Eligibility is listed as unrestricted, meaning the program is broadly open to applicant types. At the same time, applicants are advised to confirm any specific eligibility details in the full solicitation text.

What is the maximum award amount (award ceiling)?

The listed award ceiling is $1,200,000.

How many awards does NSF expect to make under this opportunity?

NSF anticipated making about 25 awards.

Are there different deadlines for HNDS-I and HNDS-R?

Yes. The posted timeline information indicates multiple deadlines depending on track. The solicitation references a deadline for direct submissions to HNDS-R and a separate deadline structure for HNDS-I proposals, with specific dates and applicability described in the solicitation.

What is the central idea behind the HNDS program?

The central idea is that many important questions about individuals and groups can now be studied in new ways because researchers can access dynamic, distributed, and highly diverse data sources. HNDS aims to use these data to produce data-rich insights about human networks and human behavior.

What kinds of outcomes does HNDS ultimately aim to support?

HNDS emphasizes knowledge that can ultimately support better outcomes in areas tied to health, prosperity, and security.

What is the main difference between "infrastructure" and "core research" in this program?

HNDS-I is oriented toward producing community-enabling resources (such as large-scale datasets, platforms, and validated tools) that others can readily use. HNDS-R is oriented toward producing theory-advancing, discipline-centered research findings within a core SBE discipline by applying network and data science methods to large, complex datasets.

Does HNDS focus only on network science, or is data science equally important?

HNDS is explicitly built around combining network science with modern data science. The program description frames the strongest opportunities as arising from pairing networked perspectives on human behavior with data-intensive scientific methods and diverse, complex data sources.

Does the opportunity description include specific submission dates?

The opportunity description indicates that there are multiple deadlines and that the specific dates and their applicability are described in the solicitation. It does not provide all specific dates in the summary provided here.

What should applicants do to confirm details not fully specified in the summary?

Applicants are advised to consult the full solicitation text for track-specific deadlines, any additional requirements, and any eligibility details that may apply despite the eligibility being listed as unrestricted.