Workshop: Towards an Ecosystem of Simulation Models and Data; 5th INFORMS Simulation Society Research Workshop; University of Durham, United Kingdom; July 31 to August 2, 2017

研讨会：走向仿真模型和数据的生态系统；

• 批准号: 1658908
• 负责人: John Shortle
• 金额: $ 0.5万
• 依托单位: George Mason University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-07-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1658908&HistoricalAwards=false
• 关键词: Workshop; Towards; Ecosystem; Simulation; Models

The objective of this workshop is to bring together researchers and students from the domains of digital simulation and data science to accelerate the concordance of these distinct but overlapping technologies. The ubiquity of data from diverse sources (sensors, social networks, Internet of Things) and evolving data-science technologies for machine learning, visual analytics, and collaborative modeling and analysis present great potential for transforming simulation practice, and both domains are crucial to the understanding and further evolution of data-driven decision support systems. As data become a ubiquitous resource, and simulation models become increasing complex, the simulation community faces major challenges and opportunities in both exploiting available real-world data and in extracting insights from the massive data sets produced from large-scale simulation experiments. The convergence of science from both research communities holds promise for tackling major research questions in both fields, such as overcoming barriers to data-driven, online simulation, assimilating and correcting data from multiple sources, simulation input uncertainty, and incorporating machine learning innovations into simulation. This award will support the participation of graduate students who will become the next generation of leaders in the simulation community.This workshop will be held at the University of Durham in the UK from July 31-August 2, 2017. It is organized by three leading simulation researchers and brings together intellectual leaders from both simulation and data science around such topics as data assimilation, data farming, online data-driven simulations, robust simulation, database technology, metamodeling, machine learning, model calibration, and collaborative modeling and simulation. The workshop organizers have identified eight topic areas, and focused groups of researchers will present and reflect upon emerging research in these areas and identify important directions for future research. The workshop will be broadly promoted through major professional societies such as the Institute for Operations Research and the Management Sciences (INFORMS), the American Statistical Association (ASA) and the Association for Computing Machinery (ACM). Results will be widely disseminated through a special issue of the ACM Transactions on Modeling and Computer Simulation.

该研讨会的目的是将来自数字模拟和数据科学领域的研究人员和学生聚集在一起，以加快这些独特但重叠的技术的一致性。 来自各种来源（传感器，社交网络，物联网）的数据无处不在，以及用于机器学习，视觉分析以及协作建模和分析的数据科学技术的发展，这对于转变模拟实践均具有巨大的潜力，并且这两个领域对于该领域至关重要，对于该领域至关重要了解和进一步发展数据驱动的决策支持系统。 随着数据成为无处不在的资源，模拟模型变得越来越复杂，模拟社区在利用可用的现实世界数据以及从大规模仿真实验中产生的大量数据集中提取见解方面面临着主要的挑战和机遇。 来自两个研究社区的科学的融合都有希望解决这两个领域的主要研究问题，例如克服数据驱动的障碍，在线模拟，从多个来源的数据，模拟输入不确定性以及将机器学习创新纳入仿真中的数据，并纠正数据。 。 该奖项将支持将成为模拟社区下一代领导者的研究生的参与。该研讨会将于2017年7月31日至8月2日在英国达勒姆大学举行。模拟研究人员围绕诸如数据同化，数据耕作，在线数据驱动的模拟，鲁棒模拟，数据库技术，元模型，机器学习，模型校准以及协作模型和仿真等主题汇集了来自模拟和数据科学的知识领导者。 研讨会组织者已经确定了八个主题领域，专注的研究人员将展示并反思这些领域的新兴研究，并确定未来研究的重要方向。 该研讨会将通过主要专业社会（例如运营研究所和管理科学研究所（Informs），美国统计协会（ASA）和计算机机械协会（ACM）等主要专业社会（ACM）。 通过有关建模和计算机模拟的ACM交易的特刊，将广泛传播结果。