DataNet Full Proposal: DataNetONE (Observation Network for Earth)

新墨西哥大学(UNM)将开发和部署DataNetONE(地球观测网络)，这是一个可持续的长期数据保存和访问网络，具有相关的搜索和发现、数据整合以及用户服务和分析工具。DataNetONE(地球观测网络)项目的目标是使科学家、决策者和公民能够了解地球变化的性质和速度，并应对相关的环境、社会和技术挑战。最初的重点将是生物和环境科学家、国家和国际研究网络以及环境观测站收集的多学科观测数据。DataNetONE将得到扩展，以直接服务于更广泛的科学领域，并通过与其他数据网络部署的互操作性来服务。该项目由新墨西哥州大学的威廉·米切纳博士指导。DataNetONE旨在通过提供对描述良好和容易发现的地球观测数据的开放、持久、可靠和安全的访问，实现对多样化和复杂的多尺度、多学科和多国家科学数据的长期保存。预期用户包括科学家、教育工作者、图书馆员、资源经理和公众。长期保存和综合获取不同和复杂的多尺度、多学科、跨国科学数据的潜在影响将在研究人员能够收集和分析数据集的速度以及他们能够解决的问题类型方面产生革命性的影响。DataNetONE将极大地促进科学研究，包括了解人口密度、大气中的氮和二氧化碳、能源消耗和全球温度之间的关系；了解和预测禽流感等疾病的出现和传播；地方或区域变化可能对地球系统的相互作用、反馈或遥相关产生重大影响的关键领域；“巨市化”对生态系统的影响；以及耦合的人与自然系统之间的相互关系。

The University of New Mexico (UNM) will develop and deploy DataNetONE (Observation Network for Earth), a sustainable long-term data preservation and access network, with related search and discovery, data integration, and user services and analytic tools. The goal of the DataNetONE (Observation Network for Earth) project is to enable scientists, decision-makers, and citizens to understand the nature and pace of change on Earth and to address associated environmental, social, and technological challenges. The initial focus will be on multi-disciplinary observational data collected by biological and environmental scientists, national and international research networks, and environmental observatories. DataNetONE will be extended to serve a broader range of science domains both directly and through interoperability with other DataNet deployments. The project is under the direction of Dr. William Michener at the UNM. DataNetONE is designed to enable the long-term preservation of diverse and complex multi-scale, multi-discipline, and multi-national science data by providing open, persistent, robust, and secure access to well-described and easily discovered Earth observational data. Expected users include scientists, educators, librarians, resource managers, and the public. The potential impact of long-term preservation and integrated access to diverse and complex multi-scale, multi-discipline, multinational science data is transformative in the speed with which researchers will be able to assemble and analyze data sets and in the types of problems they will be able to address. Scientific investigations that will be greatly facilitated by DataNetONE include understanding the relationships among human population density, atmospheric nitrogen and carbon dioxide, energy consumption and global temperatures; understanding and predicting the emergence and spread of diseases like avian flu; critical areas where local or regional changes may have strong effects on earth system interactions, feedbacks, or teleconnections; the impact of "megapolitan-ization" on ecological systems; and the interrelationships among coupled human and natural systems.