INTEROP: A Community-Driven Scientific Observations Network to Achieve Interoperability of Environmental and Ecological Data

INTEROP：社区驱动的科学观测网络，以实现环境和生态数据的互操作性

• 批准号: 0753144
• 负责人: Mark Schildhauer
• 金额: $ 75万
• 依托单位: University of California-Santa Barbara
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-08-01 至 2016-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0753144&HistoricalAwards=false
• 关键词: INTEROP; Community; Driven; Scientific; Observations

This project will build a "Scientific Observations Network"--as a multi-disciplinary, community-driven effort to define and develop a unified model for observational data, to enhance data sharing, merging and reuse in the earth and life sciences. This effort will coordinate work of a community of experts drawn from numerous disciplines, including ecology, hydrology, oceanography, geo-sciences, the geospatial community, and life sciences, working closely with computer scientists and information managers, to develop necessary specifications and technologies to facilitate intelligent interpretation and seamless integration of observational data. Advances in environmental science and ecology increasingly depend on information from multiple disciplines to address broad, complex questions about the natural world. Researchers are extremely challenged, however, in effectively locating, interpreting, and integrating data that might be relevant for these investigations. This is due to extreme variability in the structure and contents of the data that scientists collect. This project will support the growing interest in the earth and life sciences in the possibilities of describing data at the level of observation and measurement, rather than the traditional focus at the level of the data set, in order to achieve stronger data discovery and interoperability. The Scientific Observations Network will work to develop compatible, open-source, standards-based approaches to the semantic modeling of observational data. A key goal will be the development of a core conceptual data model for representing scientific observations. This core observations model will provide a common basis for developing, extending, and applying highly specialized scientific terminologies required for detailed descriptions of data relevant for environmental research. Subgroups of experts will engage in extending the core data model to include a broad range of specific measurements collected by the representative disciplines, and a series of demonstration projects will illustrate the capabilities of these approaches to confederate data for reuse in broader and unanticipated contexts. The scientific Observations Network will help to insure that scientific data, once collected, is put to the greatest possible use by the broadest group of users.

该项目将建立一个“科学观测网络”，作为一项多学科、社区驱动的努力，定义和开发观测数据的统一模型，以加强地球和生命科学领域的数据共享、合并和再利用。这项工作将协调来自众多学科的专家团体的工作，包括生态学、水文学、海洋学、地球科学、地理空间界和生命科学，与计算机科学家和信息管理人员密切合作，制定必要的规范和技术，以促进观测数据的智能解释和无缝集成。环境科学和生态学的进步越来越依赖于来自多学科的信息来解决有关自然界的广泛而复杂的问题。然而，研究人员在有效地定位、解释和整合可能与这些调查相关的数据方面面临着极大的挑战。这是由于科学家收集的数据在结构和内容上的极端可变性。该项目将支持对地球和生命科学日益增长的兴趣，即在观测和测量层面上描述数据的可能性，而不是传统的在数据集层面上的关注，以实现更强大的数据发现和互操作性。科学观测网络将致力于开发兼容的、开源的、基于标准的方法来对观测数据进行语义建模。一个关键目标将是发展一个核心概念数据模型来表示科学观测。这个核心观察模型将为开发、扩展和应用高度专业化的科学术语提供一个共同的基础，这些术语是详细描述与环境研究有关的数据所必需的。专家小组将参与扩展核心数据模型，以包括由代表性学科收集的广泛范围的具体测量，并且一系列示范项目将说明这些方法在更广泛和意想不到的环境中重用联合数据的能力。科学观测网络将有助于确保收集到的科学数据被最广泛的用户群体最大限度地利用。