对环境生态系统进行语义探索和分析

Ping Wang, L. Fu, E. Patton, D. McGuinness, F. J. Dein, R. S. Bristol
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引用次数: 6

摘要

我们的目标是为资源管理者提供决策支持工具的开发信息,这些资源管理者需要检查大型复杂的生态系统,并在面临许多权衡和冲突驱动因素时提出建议。我们采用语义技术方法,利用后台本体和不断增长的开放关联数据体。在之前的工作中,我们设计并实现了一个语义支持的环境监测框架SemantEco,并使用它来构建一个名为SemantAqua的水质门户。在这项工作中,我们大大扩展了SemantEco,以包括支持有关鱼类和野生动物物种及其栖息地的资源决策所需的知识。我们以前的系统包括支持违反环境法规和相关人类健康影响的基础本体。我们增强的框架包括支持野生动物观测和野生动物健康影响建模的基础本体,从而为更全面地研究环境污染对生态系统的影响提供更深入、更广泛的支持。我们的结果包括一个重构和扩展版本的SemantEco门户。此外,更新后的系统现在与新兴的最佳可扩展观察本体(OBOE)兼容。已纳入范围更广的相关数据,重点是增加与接触污染物有关的野生动物健康方面的数据。生成的系统存储并公开有关数据源的来源、使用方式以及选择数据的基本原理。在本文中,我们描述了该系统,突出了其研究贡献,并描述了当前和预期的使用情况。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards semantically-enabled exploration and analysis of environmental ecosystems
We aim to inform the development of decision support tools for resource managers who need to examine large complex ecosystems and make recommendations in the face of many tradeoffs and conflicting drivers. We take a semantic technology approach, leveraging background ontologies and the growing body of open linked data. In previous work, we designed and implemented a semantically-enabled environmental monitoring framework called SemantEco and used it to build a water quality portal named SemantAqua. In this work, we significantly extend SemantEco to include knowledge required to support resource decisions concerning fish and wildlife species and their habitats. Our previous system included foundational ontologies to support environmental regulation violations and relevant human health effects. Our enhanced framework includes foundational ontologies to support modeling of wildlife observation and wildlife health impacts, thereby enabling deeper and broader support for more holistically examining the effects of environmental pollution on ecosystems. Our results include a refactored and expanded version of the SemantEco portal. Additionally the updated system is now compatible with the emerging best in class Extensible Observation Ontology (OBOE). A wider range of relevant data has been integrated, focusing on additions concerning wildlife health related to exposure to contaminants. The resulting system stores and exposes provenance concerning the source of the data, how it was used, and also the rationale for choosing the data. In this paper, we describe the system, highlight its research contributions, and describe current and envisioned usage.
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