Scientific workflows improve research by reducing errors, improving outcomes, and accelerating discovery. They vary by industry and type of data, covering lab operations, computational jobs, and data analysis. Workflows standardize work and can be automated to speed up the process.
Scientific workflows are used to improve the way research is carried out. The most common types focus on lab workflows, computational workflows, and data analysis workflows. Many institutions develop scientific workflows to reduce errors, improve outcomes, and accelerate discovery. Workflows are generally designed to work with specific studies and can vary by industry and the type of data that needs to be collected and analyzed.
Scientific workflows for the lab can cover many aspects of operations. In many institutions, there are specific workflows for preparing a sample to be tested. For example, a hospital clinic may have well-defined procedures for acquiring a patient sample, registering that sample, tracking it with a scanner and barcode, storing it, and preparing it for testing. In this case, the scientific workflow may be a combination of following written procedures and computer software that tracks the sample from collection to examination. Information about the status of a sample is usually made available through a web portal for easy access. Laboratory operations also use workflows to help ensure that necessary materials are available, such as chemical reagents needed to perform a test, are in stock and available when an experiment is performed.
Another form of scientific workflow for the laboratory is related to performing the actual experiment. For example, a researcher might want to photograph a particular region of the sky or sequence the DNA of a specific cell. In both cases, a workflow would dictate the steps a researcher would take to complete the observation. For example, astronomers would need to get the coordinates of the region they want to study, input that data into the telescope’s tracking system, and position a digital camera to capture an image. These workflows can be used by an institution to schedule time on special equipment to ensure optimal use of that equipment as well.
Currently, much research is done through computer modeling and simulation. Scientific workflows for this type of research can include procedures for creating the program, troubleshooting, and then submitting and running these computational jobs. In many labs, a researcher can submit work online to a computer center. Jobs are automatically scheduled based on many factors, including priority level, available resources, and how long the job will run. In most cases, job status information is available online, so those who have submitted a job can quickly check its status to see if it is scheduled to run, run, or complete.
Once an experiment is completed, a lab test is completed, or a computer simulation is performed, another type of scientific workflow is often needed to analyze the collected data. Often, the first step in this scientific analysis workflow is to extract the data from a specific database, file, or website. Data must be placed in a suitable format. This can be something as simple as converting a temperature reading in Fahrenheit to Celsius or a distance measurement from feet to miles. The data is run through an analysis routine and may need to be compared with other data. Final results are presented to the researcher, usually in the form of a report, a file, or a visual display.
In all of these types of scientific workflows, the benefit is that researchers have standardized ways of conducting their work. In some cases, automation can be applied to some of the steps in a workflow. Automation helps to offload the researcher’s work and speed up the process.
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