Building Solutions using Science Use Case Design Patterns
The patterns detailed in the Catalog of Science Use Case Design Patterns focus on the inherent open or closed loop control problem as a common problem to be solved in reducing human-in-the-loop requirements with machine-in-the-loop capabilities. Scientific instruments, robot-controlled laboratories and edge/center computing/data resources are connected in a loop control to enable autonomous experiments, self-driving laboratories, smart manufacturing, and AI-driven design, discovery and evaluation. Each science use case design pattern consists of a behavior and a set of interfaces in the context of performing a single or a set of experiments in an open or closed loop control. The abstract design pattern definitions describe solutions free of implementation details.
The science use case design patterns are divided into two different classes: (1) Strategic Patterns that define high-level solution methods using experiment control architecture features at a very coarse granularity, and (2) Architectural Patterns that define more specific solution methods using hardware and software architecture features at a finer granularity. The Architectural Patterns inherit the features of their parent Strategic Patterns, but also address additional problems that are not exposed at the high abstraction level of the strategic patterns.
A Step-By-Step Guide discusses the involved steps in building complete solutions using the science use case design patterns, including individual decision parameters. Pattern Compositions may be required to construct complete solutions.
Creating Solutions with Design Patterns for Science Use Cases