PhysioNet, established in 1999 as the NIH-sponsored Research Resource for Complex Physiologic Signals, has attained a preeminent status among biomedical data and software resources. Its data archive was the first, and remains the world's largest, most comprehensive and widely used repository of time-varying physiologic signals. Its software collection supports exploration and quantitative analyses of its own and other databases by providing a wide range of well-documented, rigorously tested open-source programs. PhysioNet's team of researchers drive the creation and enrichment of: i) data collections that provide comprehensive, multifaceted views of pathophysiology over long time intervals, such as the MIMIC (Medical Information Mart for Intensive Care) Databases of critical care patients; ii) analytic methods for quantification of information encoded in physiologic signals relevant to risk stratification and health status assessment; iii) user interfaces, reference materials and services that add value and improve access to the resource’s data and software, and iv) unique annual signal analysis Challenges focusing on high priority clinical problems, such as early prediction of sepsis, detection and quantification of sleep apnea syndromes from a single lead electrocardiogram (ECG), false alarm detection in the intensive care unit (ICU), continuous fetal ECG monitoring, paroxysmal atrial fibrillation detection and prediction, and predicting the level of neurologic recovery from coma after cardiac arrest. PhysioNet is a proven enabler and accelerator of innovative research by investigators with a diverse range of interests, working on projects made possible by otherwise inaccessible data. PhysioNet's worldwide and growing community of users include researchers, clinicians, educators, trainees, and medical instrument and software developers. The PhysioNet enterprise was recognized with the 2016 Laufman-Greatbatch Award, the highest honor accorded by the Association for the Advancement of Medical Instrumentation (AAMI). PhysioNet Challenges received the 2022 "Distinguished Achievement Award for Data Reuse,” as part of the inaugural NIH DataWorks! Prize. PhysioNet has been designated as an NIH/NIBIB sponsored data-sharing repository. Over the next five years, we aim to: 1) magnify PhysioNet’s impact with new data and technology; 2) develop novel computational methodologies to quantify dynamical information of basic and translational value encoded in physiologic signals, and 3) harness the research community through our international Challenges that address key clinical problems, emphasizing the application of artificial intelligence methodologies.

PhysioNet, the Research Resource for Complex Physiological Signals, maintains the world's largest, most comprehensive and most widely used repository of physiological data and data analysis software, making them freely available to the research community. PhysioNet is a proven enabler and accelerator of innovative biomedical research through its unique role in providing data and other resources that otherwise would be inaccessible.