Towards Data-Driven Environmental Policy Design

西澳大利亚州政府环境和保护部(DEC)正在管理具有高度保护意义的优先领域内的环境保护资源和资金的分配。这一进程中的一个特别挑战是实际确定这些保护区内的优先生物资产，这一挑战因资源有限而加剧。在许多情况下，需要考虑到通常大量的相关参数来确定资产的优先顺序，这些参数包括资产不可替代性等量化估计以及利益相关者对相关价值(娱乐、审美)的意见。这些利益相关者包括土地所有者、当地居民和地方政府当局。该委员会制定了一个框架，要求获取人类价值，并通过动物物种和生物群落等生物资产量化其提供的价值。这些价值被用来将生物资产列为环境政策、规划和管理的关键投入。该项目的目的是提供一种方法，在现实世界环境保护的背景下捕获和汇总多个不同的数据源和任何相关的不确定性，以支持数据驱动的环境政策设计。该项目将需要DEC和英国地平线数字经济研究所的密切合作，前者在环境保护和政策设计方面贡献了他们重要的专业知识和现实世界的参与，后者利用他们在数字经济(DE)背景下的数据聚合方面的专业知识，在数字经济(DE)背景下，大量和类型的不同信息源无处不在。该项目将侧重于两个主要阶段：第一，获取关于不同生物资产所产生的人类价值的信息(及其不确定性)；第二，对收集到的定性(利益攸关方意见)和现有定量(例如，资产领域)数据及相关不确定性进行建模。在此过程中，我们将开发和评估基于模糊集合和系统和/或模糊度量和模糊积分的数据聚合算法和工具。环境保护委员会在西澳大利亚州保护区开发的框架在现实世界中的应用将为这些地区的环境政策制定提供具体支持。该项目还将在澳大利亚和国外的环境保护背景下，对已制定的框架和数据驱动的政策设计的能力提供独特的见解。所获得的知识将进一步说明，在大量利益攸关方和信息来源无处不在的其他领域，可在远程教育中设计以数据为导向的政策。

The Western Australian State Government Department of Environment and Conservation (DEC) is managing the allocation of environmental conservation resources and funds within priority areas of high conservation significance. A particular challenge in this process, exacerbated by limited resources, is the actual identification of priority biological assets within these conservation areas. In many situations, assets will need to be prioritised by taking into account the generally large number of relevant parameters which include quantitative estimates such as asset irreplaceability as well as stakeholder opinions on relevant values (recreational, aesthetical). These stakeholders include land owners, local residents and local government authorities. DEC has developed a framework which requires the capture of human values and the quantification of their delivery by biological assets such as species of animals and biological communities. The values are used to rank biological assets as a crucial input to environmental policy, planning and management. The aim of this project is to deliver a methodology to capture and aggregate multiple heterogeneous data sources and any associated uncertainty in a real world environmental conservation context in order to support data-driven environmental policy design. The project will entail a close collaboration between DEC and the UK Horizon Digital Economy Research Institute where the former contributes their significant expertise and real world involvement in environmental conservation and policy design, and the latter leverages their expertise in data aggregation in a Digital Economy (DE) context where large numbers and types of different information sources are pervasive. The project will focus on two main stages: first, eliciting information (and its uncertainty) about the human value derived by different biological assets; second, modelling the captured qualitative (stakeholder opinions) and existing quantitative (e.g. asset area) data and associated uncertainty. In doing so, we will develop and evaluate data aggregation algorithms & tools based on Fuzzy Sets and Systems and/or Fuzzy Measures & Fuzzy Integrals. The real-world application of the developed framework by DEC in conservation areas in Western Australia will provide concrete support for environmental policy-making in those areas. The project will also provide unique insights into the capacity of both the developed framework and data-driven policy design in general and in the context of environmental protection in Australia and abroad. The knowledge gained will further inform the potential for data-driven policy design in the DE in other areas where large numbers of stakeholders and information sources are pervasive.