CIF21 DIBBs: Domain-Aware Management of Heterogeneous Workflows: Active Data Management for Gravitational-Wave Science Workflows

大型数据集的分析和管理对于科学研究和教育的数据密集型领域的进展至关重要。 科学家们正在产生、分析、存储和检索大量数据。 科学数据分析的预期增长提出了管理、策展和长期获取等复杂问题。科学数据由元数据跟踪和描述。 该奖项将资助元数据感知工作流的设计、开发和部署，以管理科学分析产生的大型数据集。 用于数据分析的科学工作流程被广泛的科学家社区使用，包括天文学，生物学，生态学和物理学。使工作流元数据感知是使科学结果更容易共享，重用和支持再现性的重要一步。 该项目将利用激光干涉仪引力波观测站（LIGO）的数据，试行新的工作流程工具，这是天体物理学前沿的一个数据密集型项目。LIGO的目标是利用引力波--时空结构中的涟漪--来探索黑洞的物理学和理解引力的本质。 访问和挖掘LIGO各种引力波搜索产生的大型数据集的有效方法对于引力波物理学和天文学的整体成功至关重要。 提供这些能力将最大限度地提高NSF在LIGO的现有投资，支持LIGO科学合作组织内的新合作模式，并更好地使科学家能够向更广泛的社区解释他们的结果，包括LIGO首次探测的数据和分析来源的关键问题。 该项目涉及的跨学科合作汇集了计算和信息学理论和方法，以解决引力波物理学中的数据和工作流程管理问题。 该项目产生的研究将在科学需求识别、元数据建模、eScience工作流管理、数据来源、可重复性、数据发现和分析等方面的理论和方法上做出重大贡献。 参与该项目的LIGO科学家将确保满足社区的需求。网络基础设施和数据管理科学家将确保软件产品设计良好，并且该奖项资助的工作对更广泛的社区有用。

Analysis and management of large data sets are vital for progress in the data-intensive realm of scientific research and education. Scientists are producing, analyzing, storing and retrieving massive amounts of data. The anticipated growth in the analysis of scientific data raises complex issues of stewardship, curation and long-term access. Scientific data is tracked and described by metadata. This award will fund the design, development, and deployment of metadata-aware workflows to enable the management of large data sets produced by scientific analysis. Scientific workflows for data analysis are used by a broad community of scientists including astronomy, biology, ecology, and physics. Making workflows metadata-aware is an important step towards making scientific results easier to share, to reuse, and to support reproducibility. This project will pilot new workflow tools using data from the Laser Interferometer Gravitational-wave Observatory (LIGO), a data-intensive project at the frontiers of astrophysics. The goal of LIGO is to use gravitational waves---ripples in the fabric of spacetime---to explore the physics of black holes and understand the nature of gravity. Efficient methods for accessing and mining the large data sets generated by LIGO's diverse gravitational-wave searches are critical to the overall success of gravitational-wave physics and astronomy. Providing these capabilities will maximize existing NSF investments in LIGO, support new modes of collaboration within the LIGO Scientific Collaboration, and better enable scientists to explain their results to a wider community, including the critical issue of data and analysis provenance for LIGO's first detections. The interdisciplinary collaboration involved in this project brings together computational and informatics theories and methods to solve data and workflow management problems in gravitational-wave physics. The research generated from this project will make a significant contribution to the theory and methods in identification of science requirements, metadata modeling, eScience workflow management, data provenance, reproducibility, data discovery and analysis. The LIGO scientists participating in this project will ensure that the needs of the community are met. The cyberinfrastructure and data-management scientists will ensure that the software products are well-designed and that the work funded by this award is useful to a broader community.