SPACIOUS: Science Platform Cloud Infrastructure for Outsize Usage Scenarios

这个宽敞的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对欧空局任务数据的科学利用，该框架需要使用大数据和数据挖掘技术。通过增加大数据和数据挖掘的专业知识，并提供更容易获得这些技术的途径，Spacous将提高欧盟科学界的竞争力。为了实现这一目标，Spacous的目标是在一个新的数据挖掘环境中结合现有技术，使欧空局特派团的数据分析达到一个水平，如果没有专用的基础设施，这是不可能的。Spacous的雄心是向社区开放这个平台，同时通过与外部科学团队合作发展天体物理研究来利用数据。其主要思想是以新的方式促进和向科学界开放欧空局档案的分析。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，空间将产生不同的作用。Spacous将成为对欧空局数据产品进行大数据分析的工具。此外，我们预计，空间科学将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Spacous的关键结果。其中四个挑战将在内部定义(基于对海量GAIA和Euclid数据集的利用)，并用于推动系统的设计要求，作为大数据分析框架(BDAF)的测试案例和技术示范。在第二阶段，我们将通过公开征求建议书向社会开放该系统，并将挑选最相关的(在科学和技术上)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.