Huang Ying, Wang Xuefeng, Zhang Yi, Chiavetta Denise, Porter Alan L
Center for Studies of Information Resources, School of Information Management, Wuhan University, Wuhan, China.
Center for Science, Technology and Education Assessment (CSTEA), Wuhan University, Wuhan, China.
Scientometrics. 2022;127(9):5227-5231. doi: 10.1007/s11192-022-04507-2. Epub 2022 Aug 24.
Since the first Global Tech Mining (GTM) conference was held in Atlanta in 2011, the GTM conference has created a platform to connect tech mining researchers, exchange ideas and research progress, and promote collaborations. When it came to its 10th anniversary in 2020, COVID-19 forced the GTM conference into an online format. In tumultuous times for ST&I research activity, the GTM conference sought to focus on several issues: How to better collect and combine multiple "large data" sources? How to analyze these data effectively? And how to utilize these results more powerfully in ST&I management? In this collection, 15 papers are selected after evaluating by the science advisory committee, the guest editor team, and our peer review experts to address the following aspects regarding "tech mining": (1) DATA: Maximizing the potential of traditional and novel data; (2) METHODS: Advancing and integrating methods; (3) APPLICATIONS: Innovative analyses translating to usefulintelligence.
自2011年首届全球技术挖掘（GTM）会议在亚特兰大召开以来，GTM会议搭建了一个平台，供技术挖掘研究人员交流想法和研究进展，并促进合作。到2020年迎来其十周年之际，新冠疫情迫使GTM会议改为线上形式。在科技与创新（ST&I）研究活动的动荡时期，GTM会议力求聚焦几个问题：如何更好地收集和整合多个“大数据”源？如何有效分析这些数据？以及如何在ST&I管理中更有力地利用这些成果？在本论文集中，经过科学顾问委员会、客座编辑团队及同行评审专家评估后，挑选出15篇论文，以探讨关于“技术挖掘”的以下几个方面：（1）数据：最大化传统数据和新型数据的潜力；（2）方法：推进和整合方法；（3）应用：将创新分析转化为有用情报。
