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Randomized clinical trials have been the mainstay of clinical research, but are prohibitively expensive and subject to increasingly difficult patient recruitment. Recently, there is a movement to use real-world data (RWD) from electronic health records, patient registries, claims data and other sources in lieu of or supplementing controlled clinical trials. This process of combining information from diverse sources calls for inference under a Bayesian paradigm. We review some of the currently used methods and a novel non-parametric Bayesian (BNP) method. Carrying out the desired adjustment for differences in patient populations is naturally done with BNP priors that facilitate understanding of and adjustment for population heterogeneities across different data sources. We discuss the particular problem of using RWD to create a synthetic control arm to supplement single-arm treatment only studies. At the core of the proposed approach is the model-based adjustment to achieve equivalent patient populations in the current study and the (adjusted) RWD. This is implemented using common atoms mixture models. The structure of such models greatly simplifies inference. The adjustment for differences in the populations can be reduced to ratios of weights in such mixtures. This article is part of the theme issue ‘Bayesian inference: challenges, perspectives, and prospects’. 

During expedition MSM37 on the German RV Maria S. Merian, bottom water temperature and sediment temperature profiles were measured in the vicinity of North Pond (western flank of Mid‐Atlantic Ridge) during exploratory dives with Remotely Operated Vehicle Jason II. In addition, push cores were taken at locations with high sediment temperature gradients. We could identify two locations where sediment temperature gradients exceed 1 K/m and bottom water temperatures showed an anomaly of up to 0.04 °C above background. We interpret these observations as clear indication of low‐temperature diffuse venting of fluids that have traveled through the uppermost crust. We can safely assume that the observed phenomena are widespread at ridge flank settings where sediment cover is thin or absent, and hence, we can explain the efficient heat mining on ridge flanks. Due to the difficulties of locating diffuse low‐temperature discharge sites and due to the fact that discharge can occur through thin sediment cover as well as through sediment‐free basement outcrops, it will be very difficult to quantify fluxes of energy and mass from low‐temperature diffuse venting in ridge flank settings; however, thermal anomalies may be used to locate sites of discharge for geochemical, microbial, and hydrologic characterization.