NINDS Preclinical CDEs/Data Standards: The NIH Perspective on Common Data Elements

Why It Matters

Standardized preclinical data amplify research impact, ensure taxpayer dollars generate reusable knowledge, and accelerate therapeutic breakthroughs.

Key Takeaways

• Preclinical CDEs must align with clinical CDEs for interoperability.
• Embed data standards at experiment design to ensure FAIR compliance.
• NIH provides tools (GREI, ODSS) to assess metadata completeness.
• Budgeting and peer‑review incentives drive adoption of data standards.
• Training early‑career researchers is crucial for cultural shift.

Summary

The webinar hosted by NINDS introduced NIH’s evolving stance on common data elements (CDEs) for preclinical neuroscience, emphasizing their role in building a national, reusable biomedical data resource.

Speakers argued that CDEs must be integrated from study design, follow FAIR principles, and be harmonized with clinical CDEs to enable cross‑study comparability. NIH offers metadata schemes such as GREI and the ODSS completeness tool, and maintains repositories like FITBIR, ODC‑TBI, and ODC‑SCI for storing standardized data.

“Data aren’t a by‑product of research; they are a national resource,” noted Dr. Bellgowan, highlighting the cost of post‑hoc harmonization and the benefit of aligning outcome measures (e.g., using common water‑maze protocols). He cited the TOP‑NT program as proof that preclinical CDEs can foster collaboration.

Adoption of preclinical CDEs promises greater rigor, reproducibility, and faster translation, while satisfying taxpayer expectations for impact. Embedding standards in grant budgets, leveraging peer‑review incentives, and training the next generation are presented as the levers for a cultural shift toward systematic data sharing.

Original Description

NIH experts present the NINDS and NIH data science landscape, highlight key NIH data resources and projects, and share the NIH vision for developing and using Common Data Elements (CDEs) to enhance rigor, reproducibility, and data sharing. A panel discussion will address challenges and opportunities in aligning clinical and preclinical CDEs.