Design and implementation of a generalized laboratory data model.

摘要: Investigators in the biological sciences continue to exploit laboratory automation methods and have dramatically increased rates at which they can generate data. In many environments, themselves also evolve a rapid fluid manner. These observations point importance of robust information management systems modern laboratory. Designing implementing such is non-trivial it appears that cases database project ultimately proves unserviceable. We describe general modeling framework for data its implementation as an system. The model utilizes several abstraction techniques, focusing especially on concepts inheritance meta-data. Traditional approaches commingle event-oriented with regular entity ad hoc ways. Instead, we define distinct event schemas, but fully integrate these via standardized interface. design allows straightforward definition "processing pipeline" sequence events, obviating need separate workflow systems. A layer above schema integrates events into by defining directives", act automated managers items Directives be added or modified almost trivial fashion, i.e., without modification re-certification applications. Association between entities managed simple "many-to-many" relationships. programming interface, well techniques handling input/output, process control, state transitions. described here has served Washington University Genome Sequencing Center's primary system years. It handles all transactions underlying throughput rate about 9 million sequencing reactions various kinds per month handily weathered number major pipeline reconfigurations. basic readily adapted other high-volume processing environments.