SDCI: Data/NMI New/Improvement - Semantic Provenance Capture in Data Ingest Systems (SPCDIS)

SDCI：数据/NMI 新增/改进 - 数据摄取系统中的语义来源捕获 (SPCDIS)

• 批准号: 0968277
• 负责人: Peter Fox
• 金额: $ 56.56万
• 依托单位: Rensselaer Polytechnic Institute
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-04-21 至 2012-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0968277&HistoricalAwards=false
• 关键词: SDCI; Data; NMI; New; Improvement

Semantic Provenance Capture in Data Ingest Systems (SPCDIS)In analyzing the needs of instrument data providers, several challenges areclear:- Data is coming in faster, in greater volumes and outstripping our ability to perform adequate quality control.- Data is being used in new ways and we frequently do not have sufficient information on what happened to the data along the processing stages to determine if it is suitable for a use we did not envision.- We often fail to capture, represent and propagate manually generated information that need to go with the data flows.- Each time we develop a new instrument, we develop a new data ingest procedure and collect different metadata and organize it differently. It is then hard to use with previous projects.- The task of event determination and feature classification is onerous and we don't do it until after we get the data.These statements point to the lack of a comprehensive, re-useable data ingest framework that consists of a semantically rich set of annotations along the data ingest workflow and a smart storage, propagation and retrieval mechanism for the provenance and derivation information. For the purpose of this project, provenance is defined as: the origin or source from which something comes, its intention for use, who/what is was generated for, its manner, sense of place, and time of manufacture, production or discovery, history of subsequent owners, and documented in detail sufficient to allow reproducibility. Thus, the goal of this project is to provide an extensible representation for provenance for data ingest systems. Initially, we limit our focus to the set of solar coronal physics instruments operated at the Mauna Loa Solar Observatory in Hawaii by the High Altitude Observatory, National Center for Atmospheric Research. Over time, we will target the broader area of solar and solar-terrestrial physics, including the proposed Coronal Solar Magnetism Observatory. This project leverages innovative work with the Inference Web explanation framework which provides a set of tools for generating, validating, manipulating, summarizing, and presenting knowledge provenance. In addition we will utilize its Interlingua for provenance, justification, and trust representation - PML - the Proof Markup Language.Two important concepts to be captured are the data quality and nature of the processing stages that the data has passed through. Both qualitative and quantitative encodings of data quality are very important to a scientist determining if the data of interest are useful, applicable or accurate enough for the intended use.The provenance work will have broad applicibility since it will include domain-independent portions geared for any data ingest system as well as a domain-literate module aimed at solar and solar-terrestrial physics. This project is expected to generate a science-driven extension to PML that will provide representational primitives required for scientific provenance. The project will also contribute to community standards by adding meta data to ontologies developed in related projects with a wide degree of applicability to similar community and government programs.

在分析仪器数据提供者需求时，数据摄取系统（SPCDI）中的语义出处捕获捕获，几个挑战： - 数据越来越快地出现，更大范围，超越了我们执行适当质量控制的能力。传播需要与数据流一起使用的手动生成的信息。-每次开发新仪器时，我们都会开发一个新的数据摄取过程，并收集不同的元数据并以不同的方式组织。然后很难与以前的项目一起使用。-事件确定和功能分类的任务是繁重的，直到获得数据后，我们才能做到这一点。这些陈述表明，缺乏一个沿着数据插入工作流程以及智能存储，传播和更高的机制的信息融合的注释，这些框架由语义上丰富的注释组成。出于该项目的目的，来源被定义为：某事物的起源或来源，其使用的意图，是谁的//是什么，其方式，其方式，地位感以及制造，生产或发现的时间，后续所有者的历史记录以及足够的详细记录，足以允许可重复性。因此，该项目的目的是为数据摄取系统的出处提供可扩展的表示。 最初，我们将重点限制在国家大气研究中心高空天文台在夏威夷的Mauna LOA太阳能天文台运行的一套太阳能冠状物理仪器。 随着时间的流逝，我们将瞄准太阳和太阳透明物理的更广阔的区域，包括拟议的冠状动物磁性天文台。该项目通过推理Web解释框架利用创新的工作，该框架提供了一组工具，用于生成，验证，操纵，总结和呈现知识出处。此外，我们将利用其Interlingua进行出处，理由和信任表示 - PML-证明标记语言。要捕获的两个重要概念是数据通过的数据质量和性质的性质。对数据质量的定性和定量编码对于确定感兴趣的数据是否有用，适用或准确的科学家都非常重要。出处工作将具有广泛的应用程序，因为它将包括针对任何数据插入系统的域名插件以及任何域名插入系统以及在Solar-solar-solar-solar-perrestrestrestrestrestrestrestrestalsical interical aim aim aimain intereptys。预计该项目将产生以科学为导向的PML扩展，该扩展将为科学出处提供所需的代表性基础。该项目还将通过将元数据添加到在相关项目中开发的本体，对类似的社区和政府计划的适用性广泛。