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. In addition, the models provide an accurate visual description of the control flow for conducting biomolecular analysis using NMR spectroscopy experiment. The resulting models are correct and precise, as outside validation of the models identified only minor omissions in the models. Using the approach, we were able to accurately document, in a short amount of time, numerous steps in the process of conducting an experiment using NMR spectroscopy. Specifically, we show the application of the approach to capture the workflow for the process of conducting biomolecular analysis using Nuclear Magnetic Resonance (NMR) spectroscopy. The domain of biomolecular structure determination using Nuclear Magnetic Resonance spectroscopy is used to demonstrate the process. The approach uses three modeling techniques to model the structural, data flow, and control flow aspects of the workflow. We propose a structured process to capture scientific workflows at the conceptual level that allows workflows to be documented efficiently, results in concise models of the workflow and more-correct workflow implementations, and provides insight into the scientific process itself. While much research has been conducted on the implementation of scientific workflows, the initial process of actually designing and generating the workflow at the conceptual level has received little consideration.
Thus, scientific workflows are important for the modeling and subsequent capture of bioinformatics-related data. Workflows for experiments also highlight transitions among experimental phases, allowing intermediate results to be verified and supporting the proper handling of semantic mismatches and different file formats among the various tools used in the scientific process.
The concepts and features provided by SoftExpert Process meet all requirements established by international standards and regulations, such as BPMN, ISO 9000, ISO 14000, ISO 45001, COSO, FDA, ISO 22000, ISO 20000, ITIL, COBIT, IATF 16949, ISO/IEC 17025 and others.Scientific workflows improve the process of scientific experiments by making computations explicit, underscoring data flow, and emphasizing the participation of humans in the process when intuition and human reasoning are required. This enterprise process repository guarantees simple navigation through multiple levels of process hierarchy. Furthermore, web-based deployment makes business process knowledge permanently accessible to users. Through its central repository, SoftExpert Process allows multiple modelers to work on developing and maintaining process models concurrently.
With a comprehensive set of tools, SoftExpert Process software empowers users to model process flow, write business rules, connect to existing applications and assemble user interfaces for human interaction. SoftExpert Process is a visual, easy-to-use and advanced process modeling and analysis tool that help companies to understand, document, and deploy business and operational process better. Architecture, Engineering & Construction.Governance, Risk and Compliance Management – GRC.Environmental, Social and Corporate Governance Management – ESG.