Sharing Begins at Home: How Continuous and Ubiquitous FAIRness Can Enhance Research Productivity and Data Reuse.
Sharing Begins at Home: How Continuous and Ubiquitous FAIRness Can Enhance Research Productivity and Data Reuse.
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DOI：
10.1162/99608f92.44d21b86
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发表时间：
2022
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The broad sharing of research data is widely viewed as critical for the speed, quality, accessibility, and integrity of science. Despite increasing efforts to encourage data sharing, both the quality of shared data and the frequency of data reuse remain stubbornly low. We argue here that a significant reason for this unfortunate state of affairs is that the organization of research results in the findable, accessible, interoperable, and reusable (FAIR) form required for reuse is too often deferred to the end of a research project when preparing publications–by which time essential details are no longer accessible. Thus, we propose an approach to research informatics in which FAIR principles are applied continuously, from the inception of a research project and ubiquitously, to every data asset produced by experiment or computation. We suggest that this seemingly challenging task can be made feasible by the adoption of simple tools, such as lightweight identifiers (to ensure that every data asset is findable), packaging methods (to facilitate understanding of data contents), data access methods, and metadata organization and structuring tools (to support schema development and evolution). We use an example from experimental neuroscience to illustrate how these methods can work in practice. Imagine that you are presented with a crowded attic full of boxes of family photos and asked to assemble an accurate photographic record of some relative’s life. Most would find such a task extremely difficult. Researchers face similar challenges when attempting to comply with the data-sharing mandates that funding agencies and journals are increasingly enforcing. As they prepare a publication, they seek to assemble the data on which their results are based, but often find that these data are hard to identify, being distributed over different storage systems and labeled in ways that made sense when data was saved, but that convey little information today. Thus the data that they ultimately share are often incomplete or even inaccurate. As scientific progress depends on the ability to reproduce published research results, this situation is more than unfortunate. We suggest that this gap between intent and action is due primarily to poor process, not bad intentions, and in particular because data sharing concerns are often considered only at the end of an investigation when a publication is being prepared. We argue that the key to improved research data sharing is to adopt processes that make all data involved in a research project, in all phases, findable, accessible, interoperable, and reusable (or FAIR, in contemporary parlance). We suggest further that, just as digital cameras can simplify the family historian’s life by automatically recording a time and place for every photo, so can good tools simplify the adoption of the processes required to achieve such continuous and ubiquitous FAIRness. We use an example from a multi-year neuroscience investigation to illustrate how suitable methods and tools can result in not only better data sharing at the time of publication but also greater efficiency and effectiveness in the work of the research team over the course of a project.
