标题： 交付SKA科学 显示英文标题

标题： Delivering SKA Science

摘要： SKA将能够生成在存储和处理需求方面达到艾字节规模的科学数据产品。 这个谷歌规模的企业正在吸引来自工业界和学术界的国际广泛关注和热情。 在本章中，我们研究将在基线SKA1配置上执行的若干关键SKA调查科学项目的数据显示、存储和处理需求。 基于对HPC和存储成本趋势的一系列保守假设，以及SKA观测站内的数据流过程，显然，所提出的规模的调查项目可能会导致建设和运营成本超出当前预期的SKA1预算。 这意味着社区与SKA观测站内所包含的内容之间需要共享资源和成本，以实现SKA科学目标。 十多年前，LHC的设计者也面临类似的情况。 我们认为，现在是SKA项目和社区考虑设计和实施一个分布式SKA科学数据系统所需的努力和流程的时候了，该系统应借鉴其他项目的经验，并关注云计算技术的最新发展，以确保实现SKA科学目标的经济性、有效性和全球性。 显示英文摘要

摘要： The SKA will be capable of producing a stream of science data products that are Exa-scale in terms of their storage and processing requirements. This Google-scale enterprise is attracting considerable international interest and excitement from within the industrial and academic communities. In this chapter we examine the data flow, storage and processing requirements of a number of key SKA survey science projects to be executed on the baseline SKA1 configuration. Based on a set of conservative assumptions about trends for HPC and storage costs, and the data flow process within the SKA Observatory, it is apparent that survey projects of the scale proposed will potentially drive construction and operations costs beyond the current anticipated SKA1 budget. This implies a sharing of the resources and costs to deliver SKA science between the community and what is contained within the SKA Observatory. A similar situation was apparent to the designers of the LHC more than 10 years ago. We propose that it is time for the SKA project and community to consider the effort and process needed to design and implement a distributed SKA science data system that leans on the lessons of other projects and looks to recent developments in Cloud technologies to ensure an affordable, effective and global achievement of SKA science goals.