SPACIOUS: Science Platform Cloud Infrastructure for Outsize Usage Scenarios

SPACIOUS项目旨在通过为天体物理研究提供一个新的计算框架来促进欧空局使命数据的科学利用，这需要采用大数据和数据挖掘技术。SPACIOUS将通过增加大数据和数据挖掘专业知识并提供更容易获得这些技术来提高欧盟科学界的竞争力。为了实现这一目标，SPACIOUS的目标是将现有技术联合收割机结合到一个新的数据挖掘环境中，使欧空局任务数据的分析达到一个没有专用基础设施就不可能达到的水平。SPACIOUS的目标是向社区开放这个平台，同时通过与外部科学团队合作开展天体物理研究来利用数据。其主要想法是以新的方式促进欧空局档案的分析并向科学界开放。SPACIOUS将通过提供对数据的访问，同时提供分析这些数据的基础设施、工具和方法来发挥作用。SPACIOUS将成为对欧空局数据产品进行大数据分析的工具。此外，我们希望SPACIOUS通过影响未来处理空间科学数据的方式来做出改变。该项目的一个关键部分是产生科学价值（出版物、增强的数据产品和知识）。我们将面临重大的科学研究数据问题（挑战），其分析本身将是SPACIOUS的关键结果。其中四个挑战将在内部定义（基于对大量Gaia和欧几里得数据集的利用），并用于驱动系统的设计要求，作为大数据分析框架（BSDs）的测试用例和技术演示。在第二阶段，我们将通过公开征集提案向社区开放该系统，并将选择最相关的（科学和技术）挑战提交实施。

The SPACIOUS project aims to boost the scientific exploitation of ESA mission data by offering a new computational framework for astrophysical research that requires Big Data and Data Mining technologies to be employed. SPACIOUS will raise the competitiveness of the EU scientific community by increasing the Big Data and Data Mining expertise and providing easier access to these techniques. To reach this goal SPACIOUS aims to combine existing technologies in a new Data Mining environment to enable the analysis of ESA missions’ data up to a level which is not possible without a dedicated infrastructure. The ambition of SPACIOUS is to open this platform to the community, while at the same time exploiting the data by developing astrophysical research, in collaboration with externalscientific teams. The main idea is to facilitate and open the analysis of ESA archives to the scientific community in new ways. SPACIOUS will make the difference by providing access to the data and, at the same time, providing the infrastructure, tools and methods to analyse these data. SPACIOUS will be the tool enabling Big Data analysis of ESA data products. Furthermore, we expect SPACIOUS to make a change by influencing the future way to treat data in space science. A key part of the project is to produce scientific value (publications, enhanced data products and knowledge). We will face major scientific research data problems (challenges) whose analysis will be, per se, a key result of SPACIOUS. Four of these challenges will be defined internally (based on the exploitation of the massive Gaia and Euclid datasets) and used to drive the design requirements of the system, serving as test cases and technology demonstrators of the Big Data Analytics Framework (BDAF). In a second phase we will open the system to the community through an Open Call for proposals and will select the most relevant (both scientifically and technically) challenges submitted for their implementation.