Full name with honorifics
Marcia Lei Zeng 曾蕾,Professor Emeritus, Kent State University, USA.
美国肯特州立大学终身教授
(1)Short bio个人简介
Dr. Marcia Lei Zeng is a Professor Emeritus of Information Science at Kent State University (USA) and the recipient of the 2024 ASIS&T Award of Merit. She holds a Ph.D. from University of Pittsburgh's School of Computing and Information and M.A. from Wuhan University's School of Information Management. Her research interests include knowledge organization systems, metadata, and digital humanities, with over 150 research papers and six books. Her projects received funding from the NSF, IMLS, OCLC, Fulbright, etc. She has chaired and served on committees, working groups, and executive boards including IFLA, SLA, ASIS&T, NISO, ISO, DCMI, ISKO, iSchools, and W3C. Currently, she is chairing the DCMI Education Committee, while serving as a member of the DCMI Governing Board and ISKO Board of Directors.
Photo is available from: https://www.asist.org/2024/06/24/marcia-zeng-to-receive-the-asist-2024-award-of-merit/
曾蕾博士(Dr. Marcia Lei Zeng)是美国肯特州立大学(Kent State University)信息学院终身教授，拥有武汉大学信息管理学院硕士，美国匹兹堡大学(University of Pittsburgh)计算与信息学院博士学位。荣获国际信息科学与技术协会(ASIS&T)2024年度杰出贡献奖(ASIS&T Award of Merit), 是该奖1964年设立以来的首位华人获奖学者。她的研究与教学领域包括知识组织系统，关联数据， 元数据 ，智慧数据与大数据，数字人文中语义技术的应用等。在国内及国际刊物、百科全书、国际学术会议上发表研究文章150余篇，撰写专著六部，应邀在各国讲学和做特邀主讲，主持若干由美国国家自然科学基金会(NSF)、美国联邦博物馆和图书馆服务机构(IMLS) 、OCLC 、富布莱特(Fulbright)等资助的研究项目。曾任国际图联(IFLA)标引与分类法委员会主席、国际知识组织学会(ISKO)执行委员会理事、美国情报科学与技术学会(ASIS&T) 理事 、万维网联盟(W3C)图书馆关联数据(LLD)工作组特邀专家成员、国际联盟 iSchools数字人文课程委员会(iDHCC)主席等。参与或主持编写若干国际标准。现任国际知识组织学会( ISKO)董事会成员和都柏林核心元数据组织(DCMI)董事会成员。
(2)讲座时间与链接：
7月23日上午10:00-11:30（北京时间）
主题: Prof. Marcia Lei Zeng’s Lecture for RUC
时间: 2026年7月23日 10:00 上午 北京，上海
加入Zoom会议
https://us06web.zoom.us/j/88159432570?pwd=QGbaGWhhaD8nErqnWHh91rbfnDdt5O.1
会议号: 881 5943 2570
密码: 920291
(3)讲座内容简介
题目：Generating Smart Data for Diverse Cultural Heritage Resources in the New Era of AI -- Exploring the Opportunities and Challenges
AI时代文化遗产可信智慧数据生成 – 探讨机遇与挑战
简介:
Smart data means the trusted, contextualized, relevant, cognitive, predictive, and consumable data at any scale, revealing the most important V(value) of big data. In the new era of AI, smart data may be efficiently processed using AI technology while also being used by AI to generate intelligent applications and produce high-quality data. However, since information-bearing cultural heritage (CH) entities are usually non-textual and non-machine-readable, generating smart data for diverse CH resources presents complexities in data processing. This webinar will bring some special cases in recent innovative research projects in the world, involving processing of manuscripts (carried on different materials), symbols, images, 3Ds, sound, scent, feeling, museum objects, rock arts, etc., revealing the challenges and potentials of using AI-assisted automatic processing for them across domains.
摘要：智慧数据是指任何规模的可信的、情境化的、相关的、认知的、预测的和可消费的数据，揭示了大数据最重要的V（价值）。在人工智能新时代，智慧数据可以利用人工智能技术进行高效处理，同时也可以被人工智能用来生成智能应用，产生高质量的数据。然而，由于承载信息的文化遗产（CH）实体通常是非文本和非机器可读的，因此为不同的文化遗产资源生成智能数据会带来数据处理的复杂性。本次演讲将带来世界各地近期创新研究项目的一些特殊案例，包括手稿、象征符号、图像、3D、声音、气味、感觉、博物馆实体、壁画等物品以及跨行的研究，探讨有效方法。
核发：韩曙光 闫慧