IIS: III: Workshop on Discovery Informatics

IIS：III：发现信息学研讨会

• 批准号: 1151951
• 负责人: Yolanda Gil
• 金额: $ 9万
• 依托单位: University of Southern California
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2012-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1151951&HistoricalAwards=false
• 关键词: IIS; III; Workshop; Discovery; Informatics

The workshop aims to identify the research challenges and opportunities for transforming the scientific discovery process through advances in computing and information sciences in general, and intelligent systems in particular. It seeks to define a research agenda in Discovery Informatics. The workshop is organized around three themes: (1) efficient experimentation and discovery processes, (2) practical issues in building and refining predictive models from scientific data, and (3) social computing for science.The participants include experts and visionaries in the areas of knowledge representation and inference, machine learning and data mining, experiment design and planning, information integration, computational models of discovery, collaborative technologies, robotics, social networks, visualization, and representative application (science) domains. Research in Discovery Informatics is expected to integrate advances in multiple subdisciplines of artificial intelligence and cognitive science to develop the next generation informatics driven exploratory apparatus for scientific discovery. The resulting formal frameworks and computational tools have the potential to not only accelerate discovery but enable new modes of discovery by providing the tools that empower scientists to reach across disciplinary boundaries. Such tools can also contribute to enhanced modes of teaching and learning in science, technology, engineering, and mathematics (STEM) disciplines.The results of the workshop (including the workshop report) will be freely disseminated to the larger scientific research and educational community.

该研讨会旨在通过计算和信息科学的进步，特别是智能系统的进步，确定改变科学发现过程的研究挑战和机遇。它旨在定义发现信息学的研究议程。研讨会围绕三个主题组织：（1）有效的实验和发现过程，（2）从科学数据构建和完善预测模型的实际问题，（3）科学的社会计算。参与者包括知识表示和推理，机器学习和数据挖掘，实验设计和规划，信息集成，发现、协作技术、机器人、社交网络、可视化和代表性应用（科学）领域的计算模型。 发现信息学的研究预计将整合人工智能和认知科学的多个子学科的进展，以开发下一代信息学驱动的科学发现探索设备。由此产生的正式框架和计算工具不仅有可能加速发现，而且通过提供使科学家能够跨越学科界限的工具来实现新的发现模式。这些工具还有助于加强科学、技术、工程和数学学科的教与学模式，讲习班的成果（包括讲习班报告）将免费传播给更广泛的科学研究和教育界。