Building a Next Generation Image Repository: Molecular Annotation and Cloud-based Data Processing and Analysis

获取原始研究数据对科学事业的发展至关重要。它促进了对现有观测结果的验证，并提供了建立在这些观测结果基础上的原始材料。在生命科学领域，有许多例子表明，研究团体的成员认为某种特定类型的数据是有用的，并且有必要共享。这些数据包括基因序列、蛋白质结构数据以及基因和蛋白质表达谱。在这些情况下，社区联合起来标准化数据及其相关元数据的结构，并创建集中的存储库，以促进存储、提高可发现性，并确保数据的寿命。近年来，生命科学中的成像技术经历了一场革命，现在已被用作整个生命和生物医学科学中的定量分析技术。成像被用来理解生物体的行为，胚胎的形成，细胞的结构和动力学，以及作为生命基石的分子的功能和相互作用。成像数据集是复杂的、异构的，而且通常非常大，因此它们很少被共享或发表。基于最近几种图像数据管理技术的发展和大型数据存储设施成本的快速下降，我们建议创建一个资源来托管、服务和提供支持生命科学研究的原始科学图像数据。我们的建议基于开源技术，这些技术具有经过验证的实用程序和性能，已经运行在线资源，提供数tb的图像数据。我们建议将该资源放在EMBL-EBI，这是分子和结构生命科学数据的建立之家，并将该资源与欧洲生命科学信息学研究基础设施ELIXIR连接起来。特别是，我们将建立与已建立的分子和结构资源的链接，并努力实现这些数据的无缝集成，以便任何科学家都可以轻松地浏览，查询和计算跨几个尺度的基因组，结构和表型数据。

Access to primary research data is vital for the advancement of the scientific enterprise. It facilitates the validation of existing observations and provides the raw materials to build on those observations. In the life sciences, there are numerous examples where members of a research community determined that a particular type of data would be useful and necessary to share. These include gene sequences, protein structural data, and gene and protein expression profiles. In these cases the community united to standardize the structure of the data and its associated metadata, and to create centralized repositories to facilitate deposition, promote discoverability, and ensure the longevity of the data. Imaging in the life sciences has undergone a revolution in recent years and is now used as a quantitative assay technology throughout the life and biomedical sciences. Imaging is used to understand the behavior of organisms, the formation of embryos, the structure and dynamics of cells, and the function and interactions of molecules that are the building blocks of life. Imaging datasets are complex, heterogeneous, and often extremely large, so they are rarely shared or published. Based on the recent development of several image data management technologies and the rapidly decreasing cost of large data storage facilities, we propose to create a resource to host, serve, and make available original scientific image data that underpins life sciences research. Our proposal is based on open source technologies with proven utility and performance that already run on-line resources serving several terabytes (TBs) of image data. We propose to place this resource at EMBL-EBI, which is the established home of molecular and structural life sciences data and interface the resource with ELIXIR, Europe's research infrastructure for life science informatics. In particular we will build links with established molecular and structural resources and work towards a seamless integration of these data, so that any scientist can easily browse, query and compute on genomic, structural and phenotypic data across several scales.