tronics, energy, and medicine—and the array of exposure and hazard scenarios. The committee also identified commonalities in the research tools (for example, measurement methods and data infrastructure) throughout multiple levels of organization (for example cellular, organismal, or ecosystem) that can be capitalized on in addressing research priorities.

In the sections below, the committee expands on each of the four research priority categories and describes their relationship to the data gaps and key research questions in Chapters 3 and 4. The four categories are of equal priority and interconnected; their ordering does not imply a priority, and some research components are common to all four priority categories. In some cases, the committee describes components of the categories that need to be addressed in the short term and components that will evolve. A short-term timeframe is considered to be within 5 years. The priorities are activities that can be readily organized, resourced, and accomplished with available knowledge and tools. They need to be accomplished because they are fundamental to informing or enabling other activities. Furthermore, many topics on which research is expected to be initiated in the short term will continue to be addressed in the longer term as new tools and approaches are developed; this emphasizes the iterative nature of the research strategy.

Because of the iterative and sequential nature of the research process, the committee demarcated short-term and long-term research only when there was an evident distinction in timing. The committee describes the logical sequence of the research within each of the priority categories with recognition that timing will depend on the knowledge gained from previous research efforts.

ADAPTIVE RESEARCH AND KNOWLEDGE INFRASTRUCTURE FOR ACCELERATING RESEARCH PROGRESS AND PROVIDING RAPID FEEDBACK TO ADVANCE RESEARCH

An adaptive knowledge infrastructure is essential for supporting and providing rapid feedback on integrative research. Broadly, the infrastructure must support the generation of inputs (materials, methods, and end points), the development of relationships and models based on data-sharing and validation of the models, and the development of hypotheses and predictions from the models. The infrastructure encompasses tools, including materials, characterization methods, models, and informatics.

The infrastructure should also

•  Identify emerging data gaps and highlight those that need to be addressed.

•  Provide rapid feedback to inform research and design of new materials with reduced hazards or exposure potential.

•  Be accessible to the public and to scientists.



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