This study presents the largest human microbiota time series analysis to date, covering two individuals at four body sites over 396 timepoints. The research highlights the significant variability in an individual's microbiota across months, weeks, and even days, with only a small fraction of taxa present across all time points. The findings suggest that no core temporal microbiome exists at high abundance, although some microbes may be present but drop below detection thresholds. Many more taxa appear to be persistent but non-permanent community members. The study uses DNA sequencing and computational advances to provide high-resolution assessments of temporal variations in the human microbiome across different body habitats and individuals. This enables the identification of normal variation and pathologic states, and the assessment of responses to therapeutic interventions. The results show that microbial communities in different body sites are compositionally distinct and stable over time, with variations within sites over time. The study also reveals that the core microbiome is minimal, with the mouth having the highest core microbiota, followed by the gut and skin. Persistent and transient community members are identified, with persistent taxa appearing and remaining present, while transient taxa appear and disappear frequently. The study also shows correlations between body sites, with differences in UniFrac distances in the left and right palms being significantly correlated, possibly due to physical contact. The study's findings emphasize the importance of understanding the intrinsic variability of the human microbiome for power calculations in testing the effects of antibiotics, probiotics, and other drugs. The innovations in sequencing, cloud computing, and visualization support the development of inexpensive, informative, and personalized microbiome-based phenotyping. The study's results provide a foundation for long-term studies of variable clinical states, such as inflammatory bowel disease or drug treatments, and changes in diet or lifestyle. The study also highlights the need for further research to understand the role of low-abundance microbes in responding to changes in diet, physiological status, and other factors.This study presents the largest human microbiota time series analysis to date, covering two individuals at four body sites over 396 timepoints. The research highlights the significant variability in an individual's microbiota across months, weeks, and even days, with only a small fraction of taxa present across all time points. The findings suggest that no core temporal microbiome exists at high abundance, although some microbes may be present but drop below detection thresholds. Many more taxa appear to be persistent but non-permanent community members. The study uses DNA sequencing and computational advances to provide high-resolution assessments of temporal variations in the human microbiome across different body habitats and individuals. This enables the identification of normal variation and pathologic states, and the assessment of responses to therapeutic interventions. The results show that microbial communities in different body sites are compositionally distinct and stable over time, with variations within sites over time. The study also reveals that the core microbiome is minimal, with the mouth having the highest core microbiota, followed by the gut and skin. Persistent and transient community members are identified, with persistent taxa appearing and remaining present, while transient taxa appear and disappear frequently. The study also shows correlations between body sites, with differences in UniFrac distances in the left and right palms being significantly correlated, possibly due to physical contact. The study's findings emphasize the importance of understanding the intrinsic variability of the human microbiome for power calculations in testing the effects of antibiotics, probiotics, and other drugs. The innovations in sequencing, cloud computing, and visualization support the development of inexpensive, informative, and personalized microbiome-based phenotyping. The study's results provide a foundation for long-term studies of variable clinical states, such as inflammatory bowel disease or drug treatments, and changes in diet or lifestyle. The study also highlights the need for further research to understand the role of low-abundance microbes in responding to changes in diet, physiological status, and other factors.