UK Secretariat to support BF Collaborative Research Action on Data Management and e-Infrastructure

端到端决策支持系统在帮助社会应对全球环境变化方面至关重要。然而，这些系统的发展受到许多社会和技术挑战的阻碍，其中包括各个基础设施之间和各学科之间缺乏协调的研究战略和目标，“大数据和复杂数据”的增长远远超出传统数据处理工具的能力，主流科学家获取数据和软件工具的机会有限，以及各个基础设施、学科和规模的数据、电子基础设施和数据分析缺乏技术架构和治理的互操作性。许多国家建立了并行的电子基础设施活动，可用于开发端到端的决策支持系统。欧盟的COOPEUS、美国的EarthCube、英国的环境虚拟天文台试点项目和澳大利亚国家数据服务中心都是最值得注意的几个例子。其中大多数集中在为数据提供服务，而信息系统也需要为标准开发程度较低的模型和工具提供服务。如果要提高效率并最大限度地增加科学家在科学上所花费的时间，专注于解决所有类型的环境信息问题的跨学科、跨国家合作需要一个协调一致的规划、实施和管理方法。为制定更加协调的国际办法而开展的协调一致的国际努力有可能在数据管理、储存和共享方面产生更大的可持续性，并整合和利用现有的资源、专门知识和工具；提高标准的创建、采用和共享的速度；促进开放数据和开放源码方案，并加强能力、能力和信任，从而创建和传播一个促进全球环境变化的数据和计算科学国际实践社区。

End-to-end decision support systems are imperative in helping society respond to global environmental change. Development of these systems are impaired by numerous social and technological challenges however, and include the lack of coordinated research strategies and objectives between individual infrastructures and across disciplines, the growth of "big and complex data" to scales well beyond the capabilities of traditional data handling tools, limited access to data and software tools by mainstream scientists, and a lack of interoperability of technical architecture and of governance across individual infrastructures, disciplines and scales for data, e-infrastructures and data analytics. Many nations have instituted parallel e-infrastructure activities that can be used to develop end-to-end decision support systems. COOPEUS in the European Union, EarthCube in the US, the Environmental Virtual Observatory pilot in the UK and the Australian National Data Service, are a few of the most note-worthy examples. Most of these have concentrated on serving data, whereas information systems also need to serve models and tools, where standards are much less developed. Cross-disciplinary, cross-national collaborations focused on addressing serving all types of environmental information require a coordinated approach to planning, implementation and management if they are to be efficient and maximise the time scientists can spend on their science. A concerted international effort to develop a more coordinated international approach has the potential to produce greater sustainability in data curation, storage and sharing and to integrate and leverage existing resources, expertise and tools; increase the rate at which standards are created, adopted and shared; promote open data and open source programmes and enhance capability, capacity and trust, leading to creation and promulgation of an international community of practice in data and computational sciences for global environmental change.