Collection and evaluation of existing data: an ecological risk assessment perspective.

James T Markwiese
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引用次数: 2

Abstract

All scientific disciplines rely to some degree upon existing data to design new studies, test hypotheses, and make decisions. Because existing data can take many forms, a framework for addressing the quality of these data must be general and comprehensive. By nature of this inclusiveness, quality categories for existing data are necessarily broad. Effective employment of existing data requires the development of specific acceptance criteria from broad data quality categories. A framework is presented for collecting and evaluating existing data with examples of Environmental Protection Agency projects employing a tiered data review. The systematic planning inherent in a tiered review is described and attendant data quality considerations are developed in the context of an ecological risk assessment; specifically, the process is illustrated by defining an ecologically protective concentration of a chemical in soil.

现有数据的收集和评价:生态风险评估的视角。
所有的科学学科都在一定程度上依赖于现有的数据来设计新的研究、检验假设和做出决定。由于现有数据可以采取多种形式,因此处理这些数据质量的框架必须是通用的和全面的。由于这种包容性,现有数据的质量类别必然是广泛的。有效利用现有数据需要从广泛的数据质量类别中制定具体的接受标准。介绍了一个收集和评估现有数据的框架,并举例说明了环境保护署采用分层数据审查的项目。描述了分层审查中固有的系统规划,并在生态风险评估的背景下制定了相应的数据质量考虑因素;具体来说,这个过程是通过定义土壤中某种化学物质的生态保护浓度来说明的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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