Contents

Foreword

Executive Summary

Report

Agenda

Roster

Planning Committee

Lansdowne Conference Center
Lansdowne, Virginia

December 7–8, 1998

Research on model organisms advances the understanding of biological processes and disease states. The NIH Model Organism Database Workshop was convened to provide recommendations on reviewing and implementing genomic, genetic, and phenotypic database projects that support and provide access to research on model organisms. Several themes emerged:

• Biology-driven: The driving force of a model organism database (MOD) is the biology, not the technology. The database should allow the user to ask critical biological questions. Thus, data content, organization, currency, and accuracy are paramount. The MOD database platform should be a solid, robust product that can support the data, not a product still in an experimental stage.
• Breadth of information: MODs must contain or link to information ranging from molecular structure and function to phenotype, with both high-throughput and community-generated information. Much genetic and phenotypic information is less structured and, thus, more labor-intensive and expensive to collect and annotate than genomic data; however, it is essential that it be included.
• Curation: MODs are value-added databases; their primary function is to integrate data from disparate sources, connecting related data and enhancing its contextual information. Expert domain knowledge is essential for high-quality data capture, and this will typically require that curators have Ph.D.-level research backgrounds.
• User access: MODs must recognize the hardware, software, and network capabilities of the community they serve. In addition, it is essential that end users receive the funding to keep up with the rapidly advancing technology needed to access MODs.
• Communities: MODs must have deep ties to their organismal communities, supporting their multiple roles as data consumers, data curators, and data providers. MODs must also be able to support inquiries from broader scientific communities.
• Advisory groups: External advisory groups should provide regular advice to the MOD, the research communities, and the funding agencies. Advisory groups should include MOD users, software specialists, and representatives from other MODs.
• Priorities: MODs must set clear priorities for data content, data capture, organization, curation, annotation, navigation, and presentation.
• Database connections: MODs must establish and maintain effective cross-links among themselves as well as with other types of databases. These links enable synthetic data analysis and permit databases to share information without redundant data management.
• Leveraging existing projects: New MODs should consider affiliating with existing MODs. Existing software should be reused or adapted when possible.
• Research: Bioinformatics research is important to support the infrastructural role of the MODs. MOD projects should perform informatics research and training.

NIH Home | NHGRI Home | NHLBI Home