The 2022 NIEHS Catalytic Workshop Series on the Exposome explored the concept of the exposome and its role in understanding the interplay between environmental exposures and human health. The paper introduces two key concepts critical for exposomics research: the contribution of genetics and the environment to phenotype, and enhancing exposomic measurement at an epidemiological scale through cohort studies. The exposome-wide association study (ExWAS) is introduced as a data-driven approach for systematically discovering relationships between phenotypes and various exposures. The paper advocates for the standardized use of the term "exposome-wide association study, ExWAS" to facilitate clear communication and literature retrieval in this field. The discussion extends to emerging topics such as FAIR Data Principles, biobanked healthcare datasets, and the functional exposome, outlining future directions in exposomic research. The paper aims to guide future health researchers in understanding and evaluating exposomic studies. The exposome is defined as an individual's life-course environmental exposures, and the paper discusses the complex relationships between environmental exposures, genetic factors, and phenotypic outcomes. The paper also addresses challenges in exposome research, including the sparsity and missingness of exposure data, the need for advanced data processing techniques, and the importance of controlling for confounding variables. The paper emphasizes the importance of statistical methods such as regression analysis, variable selection, and false discovery rate control in exposome research. The paper concludes with a discussion of advanced methods in analyzing the exposome, including mixed linear modeling, survey sampling, and time-to-event outcomes. The paper highlights the importance of large-scale studies and the need for standardized approaches in exposome research. The paper also discusses the challenges of interpreting exposome-wide association studies, including the potential for false positives and the need for replication studies. The paper emphasizes the importance of data science in exposome research and the need for interdisciplinary collaboration to advance the field.The 2022 NIEHS Catalytic Workshop Series on the Exposome explored the concept of the exposome and its role in understanding the interplay between environmental exposures and human health. The paper introduces two key concepts critical for exposomics research: the contribution of genetics and the environment to phenotype, and enhancing exposomic measurement at an epidemiological scale through cohort studies. The exposome-wide association study (ExWAS) is introduced as a data-driven approach for systematically discovering relationships between phenotypes and various exposures. The paper advocates for the standardized use of the term "exposome-wide association study, ExWAS" to facilitate clear communication and literature retrieval in this field. The discussion extends to emerging topics such as FAIR Data Principles, biobanked healthcare datasets, and the functional exposome, outlining future directions in exposomic research. The paper aims to guide future health researchers in understanding and evaluating exposomic studies. The exposome is defined as an individual's life-course environmental exposures, and the paper discusses the complex relationships between environmental exposures, genetic factors, and phenotypic outcomes. The paper also addresses challenges in exposome research, including the sparsity and missingness of exposure data, the need for advanced data processing techniques, and the importance of controlling for confounding variables. The paper emphasizes the importance of statistical methods such as regression analysis, variable selection, and false discovery rate control in exposome research. The paper concludes with a discussion of advanced methods in analyzing the exposome, including mixed linear modeling, survey sampling, and time-to-event outcomes. The paper highlights the importance of large-scale studies and the need for standardized approaches in exposome research. The paper also discusses the challenges of interpreting exposome-wide association studies, including the potential for false positives and the need for replication studies. The paper emphasizes the importance of data science in exposome research and the need for interdisciplinary collaboration to advance the field.