一种描述驱动的灵活元数据跟踪方法
A Description Driven Approach for Flexible Metadata Tracking
摘要：
不断发展的用户需求提出了相当大的软件工程挑战，在数据将被存储很长时间的环境中更是如此，并且必须随着系统规范的发展而保持可用性。捕获系统的描述解决了这个问题，因为一个由解释驱动的方法使新版本的数据结构和过程能够与旧版本一起创建，从而提供对底层数据模型的改变的历史，并且使得能够捕获起源数据。本文提出了一个名为CRISTAL的系统，该系统提倡这种预防驱动的方法。CRISTAL基于推理驱动的原则;它可以使用以前版本的存储描述来定义可以以各种形式存储的各种版本的数据。为了证明这种方法的有效性，在CERN的项目的历史中，CRISTAL被用来跟踪数据和过程定义及其相关的起源数据的CMS ECAL探测器的建设，它是如何被应用于处理分析跟踪和数据索引起源的neuGRID和N4 U项目，以及它将如何在CRISTAL-ISE项目中进一步成熟。我们相信，CRISTAL方法在处理大型数据集的演变、索引和跟踪方面可能是非常宝贵的，并希望在这个方向上进一步应用它。
英文摘要：
Evolving user requirements presents a considerable software engineering challenge, all the more so in an environment where data will be stored for a very long time, and must remain usable as the system specification evolves around it. Capturing the description of the system addresses this issue since a description-driven approach enables new versions of data structures and processes to be created alongside the old, thereby providing a history of changes to the underlying data models and enabling the capture of provenance data. This description-driven approach is advocated in this paper in which a system called CRISTAL is presented. CRISTAL is based on description-driven principles; it can use previous versions of stored descriptions to define various versions of data which can be stored in various forms. To demonstrate the efficacy of this approach the history of the project at CERN is presented where CRISTAL was used to track data and process definitions and their associated provenance data in the construction of the CMS ECAL detector, how it was applied to handle analysis tracking and data index provenance in the neuGRID and N4U projects, and how it will be matured further in the CRISTAL-ISE project. We believe that the CRISTAL approach could be invaluable in handling the evolution, indexing and tracking of large datasets, and are keen to apply it further in this direction.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
