The main objectives of this article are to update the ethical standards for the conduct of human and animal biological rhythm research and recommend essential elements for quality chronobiological research information, which should be especially useful for new investigators of the rhythms of life. A secondary objective is to provide for those with an interest in the results of chronobiology investigations, but who might be unfamiliar with the field, an introduction to the basic methods and standards of biological rhythm research and time series data analysis. The journal and its editors endorse compliance of all investigators to the principles of the Declaration of Helsinki of the World Medical Association, which relate to the conduct of ethical research on human beings, and the Guide for the Care and Use of Laboratory Animals of the Institute for Laboratory Animal Research of the National Research Council, which relate to the conduct of ethical research on laboratory and other animals. The editors and the readers of the journal expect the authors of submitted manuscripts to have adhered to the ethical standards dictated by local, national, and international laws and regulations in the conduct of investigations and to be unbiased and accurate in reporting never-before-published research findings. Authors of scientific papers are required to disclose all potential conflicts of interest, particularly when the research is funded in part or in full by the medical and pharmaceutical industry, when the authors are stock-holders of the company that manufactures or markets the products under study, or when the authors are a recent or current paid consultant to the involved company. It is the responsibility of the authors of submitted manuscripts to clearly present sufficient detail about the synchronizer schedule of the studied subjects (i.e., the sleep-wake schedule, ambient light-dark cycle, intensity and spectrum of ambient light exposure, seasons when the research was conducted, shift schedule in studies involving shift work, and menstrual cycle stage in studies involving young women). Rhythm analysis of time series data should be performed with the perspective that rhythms of different periods might be superimposed upon the observed temporal pattern of interest. A variety of different and complementary statistical procedures can be used for rhythm detection. Fitting a mathematical model to the time series data provides a better and more objective analysis of time series data than simple data inspection and narrative description, and if rhythmicity is documented by objective methods, its characterization is required by relevant parameters such as the rhythm's period (tau), MESOR (time series average), amplitude (range of temporal variation), acrophase (time of peak value), and bathyphase (time of trough value). However, the assumptions underlying the time series modeling must be satisfied and applicable in each case, especially the assumption of sinusoidality in the case of cosinor analysis, before it can be accepted...