Summary

BioTeam partnered with an NIH Institute to assess the landscape of data repositories supporting a major national research program, and to chart a path toward greater interoperability across that landscape. Services included a multi-repository landscape assessment, evaluation of existing data models and access frameworks, and recommendations for a governance body to oversee data quality and FAIR compliance across the ecosystem.

The Institute funds a robust constellation of national data repositories, each shaped by years of deep domain expertise and independent innovation. BioTeam’s assessment gave the Institute leadership a clear, actionable roadmap for connecting, harmonizing, and governing these resources as a unified ecosystem, unlocking the cross-repository discoverability that modern research increasingly depends on.

Challenge

The research program drew on a wide range of data types spread across multiple independently operated national repositories. Researchers trying to work across these resources faced real friction:

• Discovery required prior knowledge of which specific repository held relevant data, since no shared “front door” existed across the ecosystem
• Each repository developed its own approach to representing clinical and research data, making it difficult to harmonize data for cross-repository analysis
• Data quality and FAIR compliance were managed independently within each repository, making it difficult to establish consistent standards and governance across the broader ecosystem
• Cloud and on-premises infrastructure varied across repositories, highlighting the need for a more consistent approach to compute environments for interactive analysis

The Institute wanted an outside, objective assessment of this landscape, one that could identify realistic paths toward interoperability without requiring every repository to abandon its existing infrastructure.

Approach

BioTeam conducted a landscape assessment across multiple national data repositories, evaluating each repository’s data model, access framework, compute environment, and interoperability posture.

A central piece of the technical work involved evaluating how clinical data (commonly represented in FHIR, the healthcare industry’s standard exchange format) could be harmonized with research data formats used across the repositories, identifying practical approaches to represent FHIR-based clinical data in formats compatible with downstream analysis pipelines.

BioTeam also evaluated compute and workspace environments already in use across the ecosystem, including cloud-based and on-premises analysis platforms, to build a clear picture of existing capabilities and where the greatest opportunity for improvement lay.

Outcomes

The assessment gave the Institute a concrete, prioritized roadmap for evolving its independently operated repositories into a connected research data ecosystem. Key recommendations included:

• Establishing a dedicated governance function to lead curation standards and FAIR compliance across the ecosystem, building on the strong foundation already in place at each repository
• Introducing a unified discovery layer that would let researchers search across repositories without needing prior knowledge of which one held relevant data
• Advancing harmonization approaches between clinical and research data formats, building toward genuine interoperability rather than one-off integrations
• Expanding programmatic API access so repositories could be queried and connected more easily by researchers and downstream tools

The engagement gave Institute leadership a realistic, evidence-based path toward a more unified research data ecosystem, with a practical framework for advancing cross-repository governance, interoperability, and FAIR data practices.