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KNOWLEDGE MANAGEMENT IN SCIENCE-POLICY PROCESS

机译:科学政策过程中的知识管理

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摘要

Environmental policies often strongly depend on environmental monitoring data, yet these increasing datasets are not always used effectively in enacting and implementing public policy. We propose a science-policy process to define the conditions that facilitate the use of scientific data for a policy. One of the most complex challenges that scientists and policy makers are facing in is that it involves knowledge management among a wide range of disciplines and actors. So a relationship between scientists and policy makers enables to translate scientific knowledge into policy-relevant scientific knowledge useful for policies. In the process, there are mainly two different types of gaps between scientific knowledge and policy-relevant scientific knowledge: direction-gap and distance-gap. Direction-gap is the situation which policy makers' requests are not clear and policy makers are not satisfied with the scientists' answers. The Distance-gap is the situation which scientists' answers are too difficult to understand for policy makers. In this paper, we focus on direction gap and suggest how scientists can be successful in bringing their knowledge and new technology to develop applications for environmental policies. We applied five attributes of "diffusion of innovation" to translating knowledge and new technology, which are: relative advantage, compatibility, complexity, trialability and observability. As a concrete example, we give suggestions to answer these five attributes in the field of remote sensing technology.
机译:环境政策通常强烈依赖于环境监测数据,但是这些不断增长的数据集在制定和实施公共政策时并不总是得到有效利用。我们提出了一项科学政策流程,以定义有助于为政策使用科学数据的条件。科学家和政策制定者面临的最复杂挑战之一是,它涉及众多学科和参与者之间的知识管理。因此,科学家与政策制定者之间的关系可以将科学知识转化为对政策有用的与政策相关的科学知识。在此过程中,科学知识与政策相关的科学知识之间的差距主要有两种:方向差距和距离差距。方向差距是指决策者的要求不清楚,决策者对科学家的回答不满意的情况。距离差距是决策者难以理解科学家答案的情况。在本文中,我们着眼于方向差距,并建议科学家如何成功地运用其知识和新技术来开发环境政策的应用程序。我们将“创新扩散”的五个属性应用于翻译知识和新技术,即相对优势,兼容性,复杂性,可试用性和可观察性。作为一个具体的例子,我们提出了一些建议来回答遥感技术领域中的这五个属性。

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