ISA, School of Physics A28, The University of Sydney, NSW 2006, Australia.
ISA, School of Physics A28, The University of Sydney, NSW 2006, Australia; School of Civil and Environmental Engineering, UNSW Australia, UNSW Sydney, NSW 2052, Australia.
Sci Total Environ. 2014 Jul 1;485-486:241-251. doi: 10.1016/j.scitotenv.2014.03.062. Epub 2014 Apr 12.
Compiling, deploying and utilising large-scale databases that integrate environmental and economic data have traditionally been labour- and cost-intensive processes, hindered by the large amount of disparate and misaligned data that must be collected and harmonised. The Australian Industrial Ecology Virtual Laboratory (IELab) is a novel, collaborative approach to compiling large-scale environmentally extended multi-region input-output (MRIO) models. The utility of the IELab product is greatly enhanced by avoiding the need to lock in an MRIO structure at the time the MRIO system is developed. The IELab advances the idea of the "mother-daughter" construction principle, whereby a regionally and sectorally very detailed "mother" table is set up, from which "daughter" tables are derived to suit specific research questions. By introducing a third tier - the "root classification" - IELab users are able to define their own mother-MRIO configuration, at no additional cost in terms of data handling. Customised mother-MRIOs can then be built, which maximise disaggregation in aspects that are useful to a family of research questions. The second innovation in the IELab system is to provide a highly automated collaborative research platform in a cloud-computing environment, greatly expediting workflows and making these computational benefits accessible to all users. Combining these two aspects realises many benefits. The collaborative nature of the IELab development project allows significant savings in resources. Timely deployment is possible by coupling automation procedures with the comprehensive input from multiple teams. User-defined MRIO tables, coupled with high performance computing, mean that MRIO analysis will be useful and accessible for a great many more research applications than would otherwise be possible. By ensuring that a common set of analytical tools such as for hybrid life-cycle assessment is adopted, the IELab will facilitate the harmonisation of fragmented, dispersed and misaligned raw data for the benefit of all interested parties.
编译、部署和利用整合环境和经济数据的大规模数据库一直是劳动密集型和成本密集型的过程，受到必须收集和协调的大量离散和不匹配的数据的阻碍。澳大利亚工业生态虚拟实验室（IELab）是一种新颖的、协作的方法，可以编译大规模的环境扩展多区域投入产出（MRIO）模型。通过避免在开发 MRIO 系统时锁定 MRIO 结构，IELab 产品的实用性得到了极大的增强。IELab 推进了“子母”构建原则的理念，即建立一个区域和部门非常详细的“母”表，从中派生“子”表以满足特定的研究问题。通过引入第三层——“根分类”——IELab 用户能够以零数据处理成本定义自己的母-MRIO 配置。然后可以构建定制的母-MRIO，最大限度地在对一系列研究问题有用的方面进行细分。IELab 系统的第二个创新是在云计算环境中提供一个高度自动化的协作研究平台，大大加快工作流程，并使所有用户都能获得这些计算优势。将这两个方面结合起来，可以实现许多好处。IELab 开发项目的协作性质使得资源得到了很大的节省。通过将自动化程序与多个团队的全面输入相结合，可以实现及时部署。用户定义的 MRIO 表，加上高性能计算，意味着 MRIO 分析将对许多比以往更广泛的研究应用有用和可访问。通过确保采用一套共同的分析工具，例如混合生命周期评估，IELab 将有助于协调分散、分散和不匹配的原始数据，使所有感兴趣的方受益。
