CASCONet：会议数据集
CASCONet: A Conference dataset
摘要：
知识动员和转化描述了将知识从研发实验室转移到可以使用的环境中的过程。人们越来越有兴趣了解知识调动机制，特别是学术界和工业界的合作。这些机制包括资助计划、研究中心和会议等。在本文中，我们专注于一个特定的知识动员机制，CASCON会议，IBM高级研究中心（CAS）的年度会议。CAS成立于1990年，其任务是促进IBM多伦多实验室与来自世界各地的大学研究人员之间的合作。第一届中国科学院大会（CASCON）于1991年中国科学院成立一年后举行。这次年会的重点是，并将继续是，汇集学术研究人员，行业从业者和技术用户在一个论坛上分享想法和展示CAS合作工作的成果。我们收集了CASCON过去25年的数据，包括论文、技术展示演示、研讨会和主题演讲的信息。由此产生的数据集称为“CASCONet”，可用于分析和与相关数据集集成。使用CASCONet，我们分析了R&D主题之间的相互作用和这些主题随着时间的推移而发生的变化。我们的分析结果表明，如何通过CAS动员知识的领域已经随着时间的推移而演变。通过将CASCONet提供给其他人，我们希望这些数据可以以其他方式用于理解这一独特背景下的知识动员和翻译。
英文摘要：
Knowledge mobilization and translation describes the process of moving knowledge from research and development (R&D) labs into environments where it can be put to use. There is increasing interest in understanding mechanisms for knowledge mobilization, specifically with respect to academia and industry collaborations. These mechanisms include funding programs, research centers, and conferences, among others. In this paper, we focus on one specific knowledge mobilization mechanism, the CASCON conference, the annual conference of the IBM Centre for Advanced Studies (CAS). The mandate of CAS when it was established in 1990 was to foster collaborative work between the IBM Toronto Lab and university researchers from around the world. The first CAS Conference (CASCON) was held one year after CAS was formed in 1991. The focus of this annual conference was, and continues to be, bringing together academic researchers, industry practitioners, and technology users in a forum for sharing ideas and showcasing the results of the CAS collaborative work. We collected data about CASCON for the past 25 years including information about papers, technology showcase demos, workshops, and keynote presentations. The resulting dataset, called "CASCONet" is available for analysis and integration with related datasets. Using CASCONet, we analyzed interactions between R&D topics and changes in those topics over time. Results of our analysis show how the domain of knowledge being mobilized through CAS had evolved over time. By making CASCONet available to others, we hope that the data can be used in additional ways to understand knowledge mobilization and translation in this unique context.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
