Open Science: A Look Into the Future of Research

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Over the past couple of years, the scientific community has been marked with the rise of a movement regarding the reproducibility of studies. This movement, formally known as Open Science, was officially born in 2015 and aims to explore ways in which science can become more collaborative, transparent, replicable, accessible, and open. It looks to challenge the traditional gatekeeping method, commonly used in the scientific world, and aims to foster a more inclusive global research environment. 

The Open Science Movement was triggered by several occurrences within the scientific community, one of which was the Replication Crisis. For years, scientists have cautioned that certain methods of collecting, analyzing, and reporting data—commonly referred to as Questionable Research Practices (QRPs)—could potentially increase the likelihood of findings seeming more statistically significant than they actually are. These worries were only heightened with a series of replication projects conducted in the 2010s, where in one of the projects, less than half of the replicated studies yielded similar results, indicating that some of the original findings were, in fact, false positives. 

The fact that scientific studies are more likely to be published if they present statistically significant results, has put additional pressure on researchers, leading some to engage in QRPs—a method of manipulating data which is not consistent with the research hypothesis. Some common examples of these practices include P-hacking and HARKing. The former refers to the process of analyzing data, relentlessly and using different methods, in order to obtain significant results. The latter, on the other hand, describes a process of presenting a post hoc hypothesis as an a priori hypothesis. 

In addition, the Digital Age has allowed people to access information from across the globe, having a large impact on the availability of scientific research online, which has given researchers the possibility to conduct science in a quick, interactive, and collaborative manner.  As a result of the aforementioned reasons, the advent of the World Wide Web can also be seen as a factor which has contributed to the initiation of the Open Science movement. 

The movement is not only about making your research available and reusable through open access, but also making your research data open by following the FAIR data principle. FAIR is an acronym which stands for Findable, Accessible, Interoperable, and Reusable. 

• Findable: research data must be described thoroughly and presented in a research data catalog, making it possible for other researchers to find it;

• Accessible: the accessibility depends on whether or not the data contains sensitive or special category information. If it does, then a confidentiality assessment needs to be made before the material is released to anyone;

• Interoperable: the researcher’s data needs to follow widely accepted standards, protocols, technologies, and mechanisms;

• Reusable: the researcher must provide a guide regarding the conditions under which the data can be used, along with information regarding the purpose of the study, the equipment and software used for data collection and analysis, etc.

Open Science aims to encapsulate the importance of being transparent in your research, as the opposite would entail creating stories rather than research. An emphasis is also placed on being open about the methods that you employ, along with an overarching goal of allowing researchers to use and reuse results from a particular study, at any point of the research process. In doing so, the experimenter ensures that their research is valuable to others from the very beginning. These methods have the potential to, not only, benefit researchers, but also have an enormous impact on society. 

Furthermore, a study conducted by Kathawalla, et al. (2021) created a guide for graduate students and their advisors to help identify the ways in which they can actively engage in open science practices. The paper highlighted the following methods:

• Journal Club: serves as a great opportunity for people to share their ideas and initiate conversations in regards to reproducibility and open science;

• Project Workflow: refers to the systematic organization and progression of projects through the various stages of the research cycle;

• Preprint: posting your manuscript before submitting it to a journal allows the researcher to get feedback, identify any flaws within the paper that might have been missed, and share their work without having to publish it;

• Reproducible Code: a detailed version of the researcher’s code can allow other researchers to generate the same outputs;

• Sharing data: making the dataset used for a project available to other researchers can help others reproduce the analyses reported and make check for quality and accuracy of the research;

• Transparent Manuscript Writing: writing a transparent and reproducible manuscript, in which the research states and justifies their decisions, allows others to better understand the research project and will make the original study more easily replicable;

• Preregistration: the process involves creating a detailed outline of the questions, hypotheses, methods, and a data analysis plan, before data collection and analysis. This minimizes the chances for the use of QRPs;

• Registered Report: involves a two-part submission process. First off, the author will create a proposal describing all of the different aspects of their research prior to data collection and analysis. Then, if the journal guarantees to publish the article, regardless of the results, authors will submit their paper with the results and discussions to the same journal. This process aims to reduce publication bias—a major issue in psychology—which refers to the selective publication of research based on the results.

With support coming from several notable organizations, such as UNESCO, Science.gov, and the European University Association (EUA), Open Science ultimately looks to “unlock” science and research between scientists and disciplines, as a method from which, hopefully, everyone can reap the benefits of. As technology continues to advance, the development of new scientific tools will allow for these fundamental principles of Open Science to be implemented and carried on. Moreover, the explosion in the interest of this movement has led to numerous new findings, methods, and practices, and there is hope for the future that all of these factors will contribute to a more transparent and collaborative system within the scientific community.

By Sara Jankovic

sara.jankovic01@icatt.it

Bibliography

Psychology Today: [Replication Crisis] https://www.psychologytoday.com/intl/basics/replication-crisis

Andrade, C. (2021). HARKing, Cherry-Picking, P-Hacking, Fishing Expeditions, and Data Dredging and Mining as Questionable Research Practices. J Clin Psychiatry. https://pubmed.ncbi.nlm.nih.gov/33999541/ 

SHB Online. (2019). Open Science: what, how, & why? [Video]. Youtube. https://youtu.be/3m6p6w8oOw4?si=85CyqbWQjgeAm7jL

The FAIR data principles. (2024). Swedish National Data Service. https://snd.se/en/manage-data/prepare-and-share/FAIR-data-principles#:~:text=FAIR%20is%20an%20acronym%20for,data%2C%20and%20possible%20to%20reuse 

Kathawalla, U., Silverstein, P., & Syed, M. (2020, May 8). Easing Into Open Science: A Guide for Graduate Students and Their Advisors. https://doi.org/10.1525/collabra.18684 

Thibault, R. T., Amaral, O. B., Argolo, F., Bandrowski, A. E., Davidson, A. R, & Drude, N. I. (2023). Open Science 2.0: Towards a truly collaborative research ecosystem. PLOS Biology. https://doi.org/10.1371/journal.pbio.3002362