Publications are the backbone of many laboratories; they’re necessary in academia to obtain grant funding, and pharmaceutical companies rely on publications to validate their clinical trial data prior to regulatory approval for any new indication. The timing of the publication is always a little tricky to nail down, though. Because research is collaborative, a slew of factors must be considered when deciding on an appropriate time to publish your research data. Of course, rarely does it ever go as planned, which is why it’s worth exploring some of the things that may help tell a researcher when it’s time to publish their data.
Science as storytelling
The ultimate goal of science is to examine some truth about how nature works. However, for any aspect of science to be properly understood, a clear and concrete story must be told regarding the experimental process, its rationale, and what the results mean. To do that, it helps to think of science writing as a form of storytelling. Every article has a flow, from introduction to methods, results, and discussion. Data from many interconnected experiments can follow a similar pattern. Looking at a single experiment without context often yields no understandable message. Together, many experiments might reveal and confirm the message that the author is hoping to convey.
However, what many scientists fail to perform effectively, especially early in their careers, is first assessing what their current research means on a broad scale, then figuring out what questions remain unanswered and how to answer them to keep building a complete story. The only concrete ways to improve this skill are by gaining experience with your subject matter and making diagrams to help explain what you see in practice. Visualization is critical to forming a scientific story because if you, the expert, can’t draw it out in simplistic terms, how are others to do so? Ultimately, visualizing your flow of data will tell you whether the story is complete or still requires experimentation to address unanswered questions.
Aging data
One of the key principles of publishing is that the study results are relevant to the current scientific landscape. Wait too long, and you risk someone publishing similar data to yours. However, the “publish or perish” mentality that is so pervasive in academia may be waning. Reproducibility is one of the most significant issues plaguing scientists today; less than 50% of all scientific studies appear to be reproducible.1,2 Publish too fast without confirming a vital result, and the risk of publishing unreproducible research increases. However, taking the time to ensure your story is both relevant and concrete is likely the better way to go. Even if your results are published second, they may either act as necessary confirmation for the first study or pose contrasting results, which elevates the relevancy of your study. Here, consistency and accuracy will play a big role in how others view your research, even if it’s produced secondary to another group’s.
Data can have an expiry date, though. The perfect example of this is in epidemiology, where long-term studies can be based on variables that just change way too fast to allow much time between data collection and publishing. Clinical studies of disease therapeutics are also subject to quick publishing for a variety of reasons: publish later and risk losing money by postponing approval for an indication. These studies are also sometimes limited by epidemiological factors, such as patient populations that may evolve over time. If a study is performed with a select patient population, it may lose relevancy if the study demographics no longer represent the real world. It’s also been found that positive clinical trial results are published much faster than negative results3; the pressure to publish a positive result about a study drug can be massive, primarily when funded by a pharmaceutical company. However, it goes without saying that the data should be adequately confirmed prior to publication, even if it’s rushed.
Other considerations
A host of other factors can determine when a study is ready for publishing. A major factor is personnel, or lack thereof. It’s common for a set of publishable results to be held up by outgoing lab personnel, like Master’s or Ph.D. students. To account for the frequent turnover of personnel, it’s worth investing in digital; using a laboratory information management system (LIMS) can save a lot of time catching up with the work previous staff has left for others to publish your research data. By standardizing results digitally across the entire lab, it’s easier to review and analyze old data compared with searching through old handwritten notebooks. LIMS can also help when there is a massive amount of unpublished data; search functions allow for easier organization of data, which makes compiling and analyzing much quicker and easier.
Finally, it might be worth sitting on certain data so that you can present it at a conference (or two or three) to gain valuable feedback from others regarding their validity and how they should best be presented. Peers are one of the most valuable resources in science, and allowing them to see the first iteration of nearly published data is an excellent way to fine-tune it.
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References:
- Begley C, Ellis L. Raise standards for preclinical cancer research. Nature. 2012;483:531-533.
- Owens B. Reliability of ‘new drug target’ claims called into question. Nature. 2011:1-5.
- Hopewell S, et al. Time to publication for results of clinical trials. Cochrane Database Syst Rev. 2007;2007(2):MR000011.
