Written by Heather F. Smith, Ph.D.
Editor-in-Chief of The Anatomical Record
Professor of Anatomy at Midwestern University
NoCTURN Open Science Committee member
ORCID: https://orcid.org/0000-0002-3738-0903
As scientists, we’ve all been there—trying to reconstruct another researcher’s steps or protocols, but missing the necessary information to verify their results. Or perhaps we hit a frustrating paywall behind which lie the keys to our continued research success. The fundamental objective of open science is to eliminate such obstacles from the scientific process.
Open science is essentially the principle and practice of making scientific discoveries and their underlying data freely accessible, which has many practical benefits for scientific progress. Broad dissemination of research findings and associated data enables other researchers to verify and reproduce the results of a study. This practice increases trust in published research and allows subsequent studies to confidently build upon them. Open science also fosters collaboration by promoting transparency, accessibility, and knowledge-sharing among scientists, while facilitating global participation in research. Data sharing also saves important resources, such as time and funding, by facilitating data reuse (i.e., recycling) by other studies, a fact that is especially important when extramural funding opportunities are limited. Beyond its practical benefits (increasing replicability, fostering collaboration, etc.), there’s also a philosophical argument to be made for open science. For taxpayer-funded research, the outcomes inherently belong to the public that paid for them. Ethically, the public deserves access to and understanding of these findings. In addition, publishing open access is also advantageous for authors, with studies demonstrating that open access papers are typically downloaded and cited at higher average rates than those published behind paywalls, likely due to increased accessibility.
In 2022, the U.S. Office of Science and Technology Policy (OSTP) released the “Nelson memorandum” which effectively requires that by 2026, the findings of all scientific studies funded by U.S. federal granting agencies be made fully accessible to the public without embargo. Several other countries have adopted equivalent requirements, and organizations such as the European Commission and G20 have endorsed comparable standards. Similarly, the United Nations Educational Scientific and Cultural Organization (UNESCO) has stated that access to information (including scientific) is a basic human right.
These various mandates and endorsements are propelling a trend in the academic publication industry toward an increase in both open access publishing and open data sharing. The FAIR Data Principles outline that for science to be truly open, it must be Findable, Accessible, Interoperable, and Reusable (FAIR), which typically involves sharing underlying data from a study as supplemental information to a published paper or via a repository or other data sharing platform. For academic journals, this has led to a push towards requesting or even requiring authors to demonstrate that they are taking active steps to make their data accessible. Most scientific journals have adopted an official data sharing policy which requires, at a minimum, that authors provide a data availability statement (DAS) indicating the availability of their data (e.g., where it can be located, whether there are stipulations to use). Other requirements range from encouraging or mandating data upload into a repository prior to publication of a paper to requiring that data be made available to the journal for peer review. Overall, most journal editors, peer reviewers, and readers of scientific papers now typically expect authors to share their data in some capacity or provide a valid and compelling explanation otherwise.
The adoption of open science FAIR principles is especially significant for promoting equitable access and participation in fields that produce extensive, shareable datasets, such as computed tomography (CT). In particular, since its outset, the CT revolution has experienced challenges with the management and dissemination of the substantial datasets it often generates. To address this issue, various initiatives have developed large-scale, openly accessible databases that connect data aggregators with repositories. For most of the CT community, an essential part of the publication process is uploading CT data and accompanying metadata to a public repository for dissemination to other researchers.
We are moving towards a world in which science is becoming progressively more open, a trend that largely benefits researchers (including CT users) and the public alike. It is often acknowledged that for the open science movement to achieve widespread success, it must scale globally and equitably. This goal presents significant logistical challenges, particularly for large CT datasets. However, with the recent creation of online repositories and the collective movement in academic journals and the CT community towards data sharing, these challenges can be overcome, ultimately resulting in more accessible CT-based science for all. Amidst current grant funding uncertainties, it is increasingly crucial for researchers to share our findings and CT data openly to enhance the collective benefits for the scientific community.