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Towards a Semantically Unified Environmental Information Space

机译:朝着语义统一的环境信息空间

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In recent years we have witnessed a proliferation of environmental information on the Web thanks to advances in automated data acquisition and to the widespread use of computer based models and decision support systems processing environmental data. The number of environmental data providers has been also increasing. However, each provider manages its own data sets encoded into specific data formats and unaware of related and relevant data managed by other providers. Also, most of the environmental data providers store their data into huge, centralized repositories, which makes the access and discovery of desired data difficult. The Linked Data principles along with the Semantic Web technologies have been recognized as a promising solution to both environmental data integration and discovery. Unique identification of environmental data by HTTP dereferencable URIs, semantic annotation of environmental data by shared domain conceptualizations (ontologies), and interlinking of related environmental data by typed (semantic) links will enable the integration of disconnected environmental data sets into the semantically unified environmental information space. Semantic annotations and semantic links will then enable semantic discovery of environmental data over such unified information space. In this paper, we try to identify a number of requirements that environmental data providers should satisfy in order to make their data fully contribute to this vision. In particular, we are focused on requirements regarding environmental data identification, representation, annotation and linking.
机译:近年来,由于自动数据采集的进步以及加工环境数据的计算机的模型和决策支持系统的广泛使用,我们目睹了网络上的环境信息扩散。环境数据提供者的数量也在增加。然而,每个提供商管理其自己的数据集编码为特定的数据格式,并且不知道其他提供商管理的相关数据和相关数据。此外,大多数环境数据提供商将其数据存储成庞大,集中的存储库,这使得访问和发现所需的数据困难。链接数据原理以及语义网络技术已被认为是对环境数据集成和发现的有希望的解决方案。通过HTTP无法转移URI的环境数据的独特识别,通过共享域概念化(本体)的语义注释环境数据,以及通过键入(语义)链路的相关环境数据的互通将使断开的环境数据集集成到语义上统一的环境信息中空间。语义诠释和语义链接将在这些统一信息空间中启用环境数据的语义发现。在本文中,我们尝试确定环境数据提供商应满足的许多要求,以便使其数据充分促进此愿景。特别是,我们专注于有关环境数据识别,表示,注释和链接的要求。

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