Collaborative Research: Building Analytical, Synthesis, and Human Network Skills Needed for Macrosystem Science: a Next Generation Graduate Student Training Model Based on GLEON

合作研究：建立分析，综合和人类网络技能需要formacrosystem科学：基于GLEONecology的下一代研究生培养模式是新的大陆规模的科学的尖端。在新兴科学网络的支持下，现在有巨大的希望了解全球环境变化对各区域和各大洲生态系统的影响和后果。来自环境传感器网络的数据，以及来自世界各地的研究和监测项目的不断增长的可用数据将支持这种理解。然而，科学的进步需要能够创造性地利用技术和数据并能够共同努力促进跨学科理解的人们。解决大规模科学问题将需要一代受过培训的科学家在团队中工作，以有效地使用/创建提供相关数据所需的网络基础设施，使用各种技术和工具探索，分析和综合这些数据，建立全球湖泊生态观测网（GLEON）研究生研究员计划（GGSFP），建议建立必要的基本技能，为新一代科学家迅速承担生产作用的宏观系统综合，和网络科学组织。GLEON是一个由科学家、信息技术专家和工程师组成的国际基层网络，他们的共同目标是建立一个可扩展的、持久的湖泊生态观测站网络。www.gleon.org GLEON拥有来自34个国家的300多名成员（95名学生），并拥有多个数据库，包括来自湖泊的近乎连续的高频数据。这项工作将结合联合收割机的广泛资源和经验，在教学法，组织社会学，领导力培训和评估的专业知识，创造一个创新的培训计划。两组研究员，沿着他们的顾问，将参加一系列的5个合作，形成其核心。提出和回答大陆规模的问题将是科学的目标。与其他主要网络教育同事的最后一次研讨会将有助于向其他生态观测站网络交流成功经验和教训。另外数十名学生将通过GLEON全体会议参加较短的培训课程。该培训计划的核心是：（1）发展对开展宏观生物学和网络科学至关重要的技术，概念和分析技能，（2）发展合作，教育和公共宣传的沟通技能，（3）积极参与现有的人员，数据和技术网络，也许最重要的是（4）专家的培训和指导，如何通过教学法、组织结构和领导力培训建立和维持人际网络。正在进行的评估将用于完善该计划，衡量成功与否，并指导未来的计划。更广泛的影响：GLEON GGSFP将培养科学家建立和维护人类基础设施的能力，这是理解全球变化下复杂环境系统功能所必需的。学生将从该计划中脱颖而出，具有在人员，基础设施，数据和设备网络中工作和利用的重要技能，以及询问和回答复杂，大规模问题的能力。数十名学生将通过GLEON参与，并将为两组10名研究员提供密集的重点培训。学生群体将被选择，以反映性别，文化和学科多样性的平衡，以下的做法培养，并与GLEON研究生协会吸取的教训。与学生的发展相一致，将成为生态社区的培训典范。该计划的成果和影响将通过网络分发合作实验室培训和通过社交网络工具在整个社区推广。此外，初级研究生顾问将体验新的培训模式和工具;研究员将在其所在机构的导师之外建立一个导师网络;研究员和初级顾问将共同编写外联材料和/或课程。通过同行评审的出版物，包括那些与组织管理有关的出版物，也将促进科学理解。该计划将成为GLEON基础设施的一部分，提供教学法，组织理论和领导力培训方面的新专业知识，从而持续生产训练有素的劳动力，其维度是实现网络科学的承诺所需的。

Collaborative Research: Building analytical, synthesis, and human network skills needed formacrosystem science: a next generation graduate student training model based on GLEONEcology is on the cusp of new continental-scale science. Enabled by emerging science networks, there is now a tremendous promise for understanding the effects and consequences of global environmental change on ecological systems across regions and among continents. Data from environmental sensor networks, as well as ever-growing, publically available data from research and monitoring programs around the world will underpin this understanding. However, scientific advances require people who can make creative use of technology and data, and who can work together to promote transdisciplinary understanding. Tackling large scale science will require a generation of scientists trained to work in teams to effectively use/create the cyber infrastructure necessary to deliver relevant data, to explore, analyze and synthesize those data using a variety of techniques and tools, and to communicate their findings to the scientific community and the public.The creation of a Global Lake Ecological Observatory Network (GLEON) Graduate Student Fellows Program (GGSFP) is proposed to build the essential skills necessary for a new generation of scientists to quickly assume productive roles in macrosystem syntheses, and network science organizations. GLEON is an international, grassroots network of scientists, information technology experts, and engineers who have a common goal of building a scalable, persistent network of lake ecology observatories (www.gleon.org). GLEON has over 300 members (95 students) from 34 countries and has multiple data repositories, including near-continuous high frequency data from lakes. This work will combine the extensive resources and experience of GLEON with expertise in pedagogy, organizational sociology, leadership training, and assessment to create an innovative training program. Two cohorts of fellows, along with their advisors, will participate in a series of 5 collaboratories that form its core. Asking and answering continental-scale questions will be the scientific goal. A final workshop with other major network education colleagues will help communicate successes and lessons learned to other Ecological Observatory Networks. Dozens of additional students will participate in shorter training sessions through GLEON all hands meetings. Central to this training program will be (1) development of technical, conceptual and analytical skills critical to carrying out macroscale biology and network science, (2) development of communication skills for collaboration, education and public outreach, (3) active participation in existing networks of people, data, and technologies, and perhaps most important (4) training and guidance by experts in how to build and sustain human networks through pedagogy, organizational structure, and leadership training. Ongoing assessments will be used to refine the program and to measure success and guide future programs.Broader Impacts: The GLEON GGSFP will develop scientists' capabilities to build and maintain the human infrastructure that is necessary to understand complex environmental system function under global change. Students will emerge from the program with significant skills in working within and utilizing networks of people, infrastructure, data and equipment, and the ability to ask and answer complex, large scale questions. Dozens of students will be engaged through GLEON, and intensive, focused training for two cohorts of ten fellows will be provided. Student cohorts will be selected to reflect gender, cultural and disciplinary diversity balance, following the practices fostered, and lessons learned with the GLEON Graduate Student Association. Coincident with the development of students will be a training exemplar for the ecological community. The outcomes and impact of this program will be extended throughout the community via web-distribution of collaboratory training and through social networking tools. In addition, primary graduate student advisors will experience new training models and tools; fellows will develop a network of mentors in addition to those at their home institution; and fellows and primary advisors, together, will develop outreach materials and/or curricula. Advances in scientific understanding through peer reviewed publications, including those having to do with organizational management will also result. The program will become part of the infrastructure of GLEON, providing new expertise in pedagogy, organizational theory, and leadership training, resulting in continued production of a highly trained work force with the dimensionality required to realize the promise of network science.