TR&D2: Ontology and software tools describing reproducibility, credibility, and biosimulation

NIH RePORTER · NIH · P41 · $332,423 · view on reporter.nih.gov ↗

Abstract

TECHNOLOGY RESEARCH & DEVELOPMENT 2: Project Summary Biosimulation model repositories continue to grow, but unfortunately, the value of these models is impeded by persistent challenges with reproducibility and credibility of models. Although we know how to make models more reproducible, the community needs improved repositories and tools to capitalize and implement these ideas. This technology development project will provide key standards and tools for semantic annotation. Clear, unambiguous annotation of models is a key technology in making models more understandable, findable, and reusable. The goals of this project include: (1) Standards and ontologies that assist with model management. These capture the semantics behind model evolution and versioning, allowing users to understand which version of which models might be appropriate. (2) Standards and ontologies for model composition and decomposition, even when models are developed with different mathematical paradigms. (3) Tool support for automatic model annotation recommendations, to reduce the cost and burden of semantic annotation. (4) Standards and repositories that capture model execution, including new development of the SED-ML standard.

Key facts

NIH application ID
10780532
Project number
2P41EB023912-06
Recipient
UNIVERSITY OF WASHINGTON
Principal Investigator
JOHN H. GENNARI
Activity code
P41
Funding institute
NIH
Fiscal year
2024
Award amount
$332,423
Award type
2
Project period
2018-06-13 → 2029-03-31