From the Reproducibility Initiative to F1000 Research’s Preclinical Reproducibility and Robustness channel, much attention in the life science community has been focused on study reproducibility. These highly publicized efforts cover actions that only a subset of members of the community can take, such as validating important studies and publishing negative results.
But data quality is the responsibility of every scientist at the bench, so what can the whole community do?
This is a question that Artel has started to explore—understanding what scientists are doing to ensure reproducibility and good data quality. To get the conversation started we conducted a survey to find out what bench scientists think about data quality, variability, and reproducibility. For example, what factors did our survey respondents think contribute most to variability? What actions did they take to improve reproducibility, and did those actions really address the critical concerns?
To see what our respondents had to say, download the survey report. And then come back to the Artel Digest—we’ll be continuing the conversation through stories with scientists about what they’re doing to ensure high quality data.