NIAID Blueprint

A Blueprint for Including Digital Objects in the NIAID Data Ecosystem

About the Blueprint

In 2023, GO FAIR US (GFU) was awarded a fully funded research subcontract to conduct data landscaping work for the National Institute of Allergy and Infectious Diseases (NIAID). The work is sponsored by the NIAID Office of Data Science and Emerging Technologies (ODSET) and funded on NIAID’s behalf by the Frederick National Laboratory for Cancer Research, operated by Leidos Biomedical Research, Inc. GFU collaborates with the GO FAIR Foundation, the National Center for Atmospheric Research (NCAR), the Ronin Institute, and other partner consultants.

The NIAID Data Landscaping and FAIRification project uses the FAIR principles (Findable, Accessible, Interoperable, and Reusable) to increase use of and improve metadata in NIAID and NIH-supported repositories and data resources. The project aims to:

Improve metadata quality across NIAID and NIH-supported repositories, so data is easier to find and use.

Support NIAID's mission to better understand, treat, and prevent infectious, immunologic, and allergic diseases.

Enable impactful research by helping researchers use NIAID resources for secondary research and reuse of existing data.

Make NIAID's ecosystem FAIR-enabled by providing guidance so its integrated data, tools, and services follow FAIR practices.

Offer structured training for stakeholders, building on GO FAIR's model of M4M workshops and FAIR Implementation Profiles (FIPs).

From FAIR to Blueprint

Phase I: Oct 2024 - Aug 2025

Analyzed 9 repositories, created FIPs and Work Plans, and produced the Blueprint

Phase II: Sep 2025 - May 2026

Training, outreach, stakeholder alignment, and publications

A generic Blueprint for the wider research data ecosystem

How we got here

Our approach, Work Plans, and the pivot to recommendations

Research and surveys

Guided by the FAIR principles, the team analyzed the purposes, needs, and capabilities of 11 key NIAID repositories.
The approach was iterative, beginning with desk-based research and surveys of each repository.
Findings were used to create FAIR Implementation Profiles (FIPs) and detailed Work Plans with practical strategies for repositories to improve their FAIRness (Hoebelheinrich et al., 2026).

From assessment tools to community practice

The team first assessed off-the-shelf tools for quantifying the FAIRness of repositories.
It ultimately turned to more community-centric practices for evaluating and improving repositories (Hoebelheinrich et al., 2025).

From asessments to recommendations

While creating the Phase I Work Plans, GFU and ODSET pivoted from repository-specific FAIR assessments to a shared list of recommendations for NIAID repositories.
The result was A Blueprint for Including Digital Objects in the NIAID Data Ecosystem, or "the Blueprint."
Phase II builds on the Blueprint through training, outreach, stakeholder alignment, and publications.

View the 9 target repositories

Table 1: Phase I repositories by division

Table 1. Phase I’s 9 target repositories

Division/ Office	Resource	Description
OCICB	AccessClinicalData @NIAID (ACDN)	Clinical trials data, including COVID-19 and other sponsored clinical trials data, with recent focuses on longitudinal immune responses and adaptive treatment to COVID-19
	TB Portal	Genomics, clinical data, imaging information from tuberculosis (TB) patient cases, focus on advancement of TB research for public health
DAIT	IEDB	Immunology, experimental data on antibody and T cell epitopes with a focus on autoimmunity, infectious disease, allergy, and transplantation
	ImmPort	Bioinformatics for immunology, with a focus on data discoveries from research organizations and scientists
	ImmuneSpace	Provides access to data generated by Human Immunology Project Consortium centers
	ITN Trialshare	Clinical science and immunology, with a focus on the advancement of immune tolerance therapies and biomarker development
DAIDS	ACTG	Global clinical trials network to improve the management of HIV and its comorbidities; develop a cure for HIV; and innovate treatments for tuberculosis, hepatitis B, and emerging infectious diseases.
	MACS WHIS Combined Cohort Study (MWCCS)	Basic science, clinical science, and epidemiology of HIV infection in the U.S., with a focus on comorbidities among those living with HIV
DMID	Bioinformatic Resource Centers (BRCs)	Bioinformatics resource centers including bacterial and viral infectious diseases, assisting researchers with analyzing genome sequences