Linked Science is the practice of inter-connecting scientific assets by publishing, sharing and linking scientific data and processes in end-to-end loosely coupled workflows that allow the sharing and re-use of scientific data. Much of this data does not live in the cloud or on the Web, but rather in multi-institutional data centers that provide tools and add value through quality assurance, validation, curation, dissemination, and analysis of the data. In this paper, we make the case for the use of scientific scenarios in Linked Science. We propose a scenario in river-channel transport that requires biogeochemical experimental data and global climate-simulation model data from many sources. We focus on the use of ontologies—formal machine-readable descriptions of the domain—to facilitate search and discovery of this data. Mercury, developed at Oak Ridge National Laboratory, is a tool for distributed metadata harvesting, search and retrieval. Mercury currently provides uniform access to more than 100,000 metadata records; 30,000 scientists use it each month. We augmented search in Mercury with ontologies, such as the ontologies in the Semantic Web for Earth and Environmental Terminology (SWEET) collection by prototyping a component that provides access to the ontology terms from Mercury. We evaluate the coverage of SWEET for the ORNL Distributed Active Archive Center (ORNL DAAC).

中文翻译：

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关联科学调查：利用语义技术加强气候变化数据发现。

链接科学是通过在端到端松散耦合的工作流程中发布、共享和链接科学数据和流程来互连科学资产的实践，从而允许共享和重用科学数据。这些数据大部分并不存在于云端或网络上，而是存在于多机构数据中心中，这些数据中心提供工具并通过数据的质量保证、验证、管理、传播和分析来增加价值。在本文中，我们阐述了在关联科学中使用科学场景的案例。我们提出了一个河道运输场景，需要来自多个来源的生物地球化学实验数据和全球气候模拟模型数据。我们专注于使用本体（领域的正式机器可读描述）来促进这些数据的搜索和发现。Mercury 由橡树岭国家实验室开发，是一种用于分布式元数据收集、搜索和检索的工具。Mercury 目前提供对超过 100,000 条元数据记录的统一访问；每月有 30,000 名科学家使用它。我们通过构建一个组件原型来增强 Mercury 中的本体搜索，例如地球和环境术语语义网 (SWEET) 集合中的本体，该组件提供对 Mercury 本体术语的访问。我们评估了 ORNL 分布式主动归档中心 (ORNL DAAC) 的 SWEET 覆盖范围。