Data commons for 'omic, microscopy and analysis core facilities

描述：我们提出了一个“数据共享”，为七个核心设施提供数据存储，这些设施为杜克大学的生物医学研究人员及其全球合作者产生或分析大型复杂数据集。随着数据存储需求已经达到数百tb，核心设施继续采用新技术，这将进一步增加数量级的数据流，这对数据保留和分析来说是一个迫在眉睫的挑战。我们的建议旨在将这些多余的数据从对生命科学研究人员的挑战转变为优势。使用NIH SIG拨款购买的设备将使用磁盘阵列（~450 tb可用）和磁带库的混合，初始未压缩数据容量为1 pb，以创建可扩展的数据存储资源，具有保护和保存数据和有效管理数据的功能。磁盘阵列将被配置为向现有的计算服务器提供数据，供研究人员或杜克大学“组学分析核心设施”的工作人员进行分析，该设施于2012年创建，旨在为不熟悉基因组数据集的研究人员提供支持。磁盘阵列和磁带库将在量子“Stornext”文件系统中以协调的方式运行，数据管理策略和系统使用数据收集将允许对系统性能和经济性进行细粒度优化。量子系统已广泛应用于数据密集型行业和研究，包括基因组科学。从一开始，核心设施就会使用这些设备来加强它们的整合。杜克大学快速数据存储库的数据来源和管理功能（自2006年以来一直由蛋白质组学和微阵列核心设施使用）将附加到拟议的存储设备上，以便服务可以扩展到包括序列数据、RNAi筛选数据、显微镜图像和分析核心的结果。因此，建议的数据共享将以一种允许在受保护的存储框架内进行有效的（在许多情况下）自动数据切换的方式运行。这种集成消除了数据集成的后勤障碍，减少了意外（或恶意）数据损坏的机会，并增强了大型研究项目自动化的范围。存储将通过核心连接到数据生成设备和由组学分析核心运行的计算服务器，以及高性能分析集群上的存储。所有IT资产，包括提议的设备，都由专业IT人员管理，这些人员在基因组科学的大规模研究所需的基础设施方面具有特别的实力。虽然数据管理效率的提高将是一个直接的好处，但该项目的更重要目标是使研究人员能够加速使用综合和复杂的数据，以探索人类健康和疾病的复杂性。

DESCRIPTION: We propose a "data commons" to provide data storage for seven core facilities that produce or analyze large and complex datasets for biomedical researchers at Duke University and their collaborators worldwide. With data storage requirements already counting in hundreds of terabytes the core facilities continue to adopt new technologies that will further increase the flows of data by orders of magnitude, a looming challenge for data retention and analysis. Our proposal seeks to turn this excess of data from a challenge to strength for life sciences researchers. Equipment purchased with the NIH SIG grant will use a mixture of disc arrays (~450 usable terabytes) and tape library with initial uncompressed data capacity of 1 petabyte to create a scalable data storage resource with features that protect and preserve data and manage data efficiently. Disc arrays will be configured to serve up data to existing computational servers for analysis either by researchers or by staff in Duke's "Omics Analysis Core Facility," which was created in 2012 to provide support to researchers unfamiliar with using genomic data sets. The disc arrays and tape library will function in a coordinated fashion in a Quantum "Stornext" file system, and data management policies and system usage data collection will allow for fine-grained optimization of system performance and economy. The Quantum systems have been widely deployed in data-intensive industry and research, including in the genome sciences. From the outset, the core facilities will use the equipment to enhance their integration. Data provenance and management features of the Duke's Express Data Repository - used by the proteomics and microarray core facilities since 2006 - will be attached to the proposed storage equipment so that services can be expanded to include sequence data, RNAi screening data, microscopy images, and results from the analysis core. Thus, the proposed data commons will function in a manner allowing for efficient and, in many cases, automatic data hand-offs within a protected storage framework. This integration removes logistical impediments for data integration, reduces chances for accidental (or malicious) data corruption, and enhances the scope of automation for large-scale research projects. The storage will be connected via the cores to data-producing equipment and to computational servers run by the 'omics analysis core and to storage on a high-performance analysis cluster. All IT assets, including the proposed equipment, are administered by professional IT staff with particular strength in infrastructure required for large-scale research in the genome sciences. While increase in efficiency of data management will be an immediate benefit, the more important goal of the project is to enable researchers to speed their use of integrated and complex data to explore the complexity of human health and disease.