It’s been a challenging 18 months for science educators and those running research facilities. The global COVID-19 pandemic made in-person lab work impossible under many circumstances and difficult in the best of conditions. Now, as researchers and students begin to return to the lab, an opportunity presents itself for a fresh start. One way in which labs are refreshing their approach to research and education is by adding software and equipment that allows for the automation of procedures and analysis with the goal of increasing repeatability and reproducibility within experiments and research.
Crisis of reproducibility
The phrases “reproducibility crisis” and “replication crisis” became buzzwords in the scientific community in the 2010s, with that notoriety spilling over into both the scientific and mainstream media’s coverage of the sciences. Several high-profile scientific and sociological studies were called into question when researchers were unable to reproduce their results. In 2015, a group of psychology researchers under the moniker of the “Open Science Collaboration” found that they were only able to reproduce the findings of 68% of studies published in high-ranking peer-reviewed journals. A 2016 survey of 1,576 researchers by the journal Nature similarly found that 52% agreed that there was a “crisis” of reproducibility, though most said they still trusted published research.
The automated advantage
One step that researchers can take to ensure the reproducibility of their experiments and thereby boost the integrity of their data and conclusions is by automating procedures, workflow, and record keeping. These steps not only reduce the possibility for human error, but also provide a clear roadmap for future researchers to repeat processes in the lab to review and test results. The National Academies of Sciences, Engineering, and Medicine guide Reproducibility and Replicability in Science (National Academies Press, 2019) outlines several of the ways in which automation is being used to enhance reproducibility of research results, including record keeping, data analysis, data version control, and workflow management. The publication notes that “automated scientific workflows are essential in data-intensive and large-scale science missions that aim to be computationally reproducible.”
A 2019 study by researchers at the Indiana University School of Informatics, Computing, and 
Engineering employed these techniques to demonstrate “how automation can be used to address many of these factors contributing to the replication crisis.” The study focused on the controlled rearing of chicks, comparing automated and non-automated research methods. The study found that the automated tracking system allowed researchers to increase the amount of data collected from each test subject, which in turn “reduced measurement error by 60% and increased the effective size of experiments by about 300%.”
An automated refresh
BIOPAC’s AcqKnowledge data acquisition and analysis software allows labs of any size to gain the advantage of automation to improve both the efficiency and effectiveness of research. Features like Batch Processing and BIOPAC Basic Scripting help eliminate the potential for human error by consolidating multiple tasks into a single automated routine. A heightened level of standardization and consistency results in improved data quality. Adding a Basic Scripting license to AcqKnowledge 5.0.6 ensures results are reproducible regardless of who is carrying out the experiment.
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