![]() ![]() However, there is no widely acceptable method of codifying that model by writing it down in concrete format. Įxperienced scientists usually have a mental conceptual model of the workflow of an experiment. For instance, the Construct Spectrum step of the conceptual model could be implemented using the NMRPipe tool. The implementation model describes the software, network access, database, and other resources needed to implement the workflow. The implementation model describes the execution of the steps used to carry out the process described in the conceptual model. For instance, in the analysis of biomolecules using NMR spectroscopy, one step in the conceptual model might be Analyze Sample which encompasses the tasks of Construct Spectrum, Analyze Spectrum, Assign Peaks, Post Process Sample, and Validate Data/Results. ![]() The conceptual model describes what steps need to be taken in order to complete an experiment. In addition, once a conceptual model has been validated, it can be mapped to different implementations in different experiment environments. The separation of the conceptual model from the implementation model allows the steps of the experiment process to be understood without constraints imposed by the implementation. As such, a conceptual model highlights the data that flow through the workflow. A conceptual model of a scientific workflow captures the researcher's understanding of what an experiment does and how it works without capturing implementation details. In contrast, a conceptual model of a workflow focuses on the user's viewpoint without being tied to a particular set of underlying implementation tools. An implementation model of a workflow is tied to a specific set of tools to be used to carry out an experiment. Scientific workflow environments result in the creation of an implementation-level workflow, a workflow that represents how the system will carry out the tasks in the workflow. Currently, most workflows created for scientific experiments are constructed using a scientific workflow environment such as Kepler. The workflow for a scientific experiment can be modeled at two levels of abstraction the implementation level and the conceptual level. Scientific workflows are complex, dynamic, and contain a high degree of variation. While workflows found in the business world typically represent a consistent, repeatable sequence of events that operates on homogeneous data and conducts simple computations, scientific workflows represent a scientific experiment which can contain numerous unknowns, may have variability in execution sequence, operate on heterogeneous data, contain complex computations, and require a considerable degree of intuition on the part of the researcher to be executed successfully. Scientific workflows are becoming much more widely used to concisely describe the activities required to execute scientific experiments. ![]()
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