Superfund Research Program, National Institute of Environmental Health Sciences (NIEHS), National Institutes of Health (NIH), Department of Health and Human Services (DHHS), Research Triangle Park, NC, USA.
MDB, Inc., Durham, NC, USA.
Rev Environ Health. 2020 Jun 25;35(2):111-122. doi: 10.1515/reveh-2019-0089.
The National Institute of Environmental Health Sciences (NIEHS) Superfund Basic Research and Training Program (SRP) funds a wide range of projects that span biomedical, environmental sciences, and engineering research and generate a wealth of data resulting from hypothesis-driven research projects. Combining or integrating these diverse data offers an opportunity to uncover new scientific connections that can be used to gain a more comprehensive understanding of the interplay between exposures and health. Integrating and reusing data generated from individual research projects within the program requires harmonization of data workflows, ensuring consistent and robust practices in data stewardship, and embracing data sharing from the onset of data collection and analysis. We describe opportunities to leverage data within the SRP and current SRP efforts to advance data sharing and reuse, including by developing an SRP dataset library and fostering data integration through Data Management and Analysis Cores. We also discuss opportunities to improve public health by identifying parallels in the data captured from health and engineering research, layering data streams for a more comprehensive picture of exposures and disease, and using existing SRP research infrastructure to facilitate and foster data sharing. Importantly, we point out that while the SRP is in a unique position to exploit these opportunities, they can be employed across environmental health research. SRP research teams, which comprise cross-disciplinary scientists focused on similar research questions, are well positioned to use data to leverage previous findings and accelerate the pace of research. Incorporating data streams from different disciplines addressing similar questions can provide a broader understanding and uncover the answers to complex and discrete research questions.
美国国家环境卫生科学研究所（NIEHS）超级基金基础研究与培训计划（SRP）资助了广泛的项目，涵盖了生物医学、环境科学和工程研究领域，并生成了大量由假设驱动的研究项目产生的数据。对这些多样化的数据进行组合或整合，为揭示新的科学关联提供了机会，这些关联可用于更全面地了解暴露与健康之间的相互作用。整合和再利用该计划内各个研究项目生成的数据需要协调数据工作流程，确保数据管理和分析核心在数据管理方面采用一致且稳健的实践，并从数据收集和分析的初始阶段就开始进行数据共享。我们描述了利用 SRP 内部数据以及当前 SRP 努力来推进数据共享和再利用的机会，包括开发 SRP 数据集库以及通过数据管理和分析核心促进数据整合。我们还讨论了通过识别健康和工程研究中捕获的数据之间的相似之处、为暴露和疾病建立更全面的图景、利用现有的 SRP 研究基础设施来促进和促进数据共享，从而改善公共卫生的机会。重要的是，我们指出，虽然 SRP 具有利用这些机会的独特地位，但这些机会可以应用于整个环境卫生研究领域。由专注于相似研究问题的跨学科科学家组成的 SRP 研究团队，非常适合利用数据利用以前的研究结果并加快研究速度。整合来自不同学科的数据流，这些学科都在解决类似的问题，可以提供更广泛的理解，并揭示复杂和离散研究问题的答案。
