The complexity, scope, and scale of scientific research have expanded substantially. During the past several decades, there has been increasing prevalence of large, international, multicenter clinical trials; multidisciplinary investigations involving interventional studies or observational research; and studies that combine large data sets (“big data”) from multiple cohorts or research consortia and use sophisticated analytic methods, such as in some studies involving genomic research or machine learning. This trend toward increasingly collaborative research involving multiple investigators and research groups has been referred to as group science, ensemble science, or more commonly, team science.1 How authors and nonauthor collaborators can be identified in publications to ensure appropriate credit and recognition of team science is evolving, can be challenging, and is of great importance to the scientific community and individual investigators.
This editorial is a reliable and useful example for grappling with the issues associated with very large collaborations. It is a recommended inclusion in institutional research integrity resource libraries and has been added as essential reading in the AHRECS Resource Library
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Team science also creates potential challenges, including identifying the optimal group of investigators to address the study questions of interest; rigorously addressing issues of heterogeneity in attempts to combine data or data sets; ensuring engagement, appropriate participation, and supervision of all members of the scientific team; reaching agreement and consensus regarding presentation and interpretation of study findings; and appropriately recognizing the contributions of individual members of the research team in scientific publication.
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