Beyond Translation

Translating VRA Core 4.0 into Chinese

  • Xiaoli Ma University of Florida
Keywords: VRA Core 4.0, metadata schema element translation, traditional Chinese, simplified Chinese


Developed in 1996, the VRA (Visual Resources Association) Core, now in its fourth version, is an internationally recognized metadata standard for describing works of visual culture and their surrogates. It has been integrated into schemes and tools to record cultural objects and related media files for decades. The primary document, VRA Core 4.0 Element Description and Tagging Examples (VRA Element Description), was first made available in English, followed by Italian and Greek. To expand its global influence, VRA has long sought to have its metadata standard translated into additional languages, including Chinese. Starting in early 2021, members of the VRA Cataloging and Metadata Standards Committee worked with a team of metadata practitioners to translate this document, inviting scholars and practitioners in the U.S., Taiwan, and mainland China to review translation drafts. Following an 18-month effort, VRA Element Description became available on the Library of Congress website ( on August 15, 2022 in both traditional and simplified Chinese. This article explores the origin and trajectory of the project and delves into the challenges encountered by the core team and reviewers at various phases. Key discussion points include the difference between the two language systems (traditional and simplified Chinese), the processes for selecting Chinese terms that share similar connotations with the original English terms, the role of reviewers in refining the drafts, and the unexpected difficulties in formatting the final versions.


My sincere thanks go to Lisa Gavell at ITHAKA as this article could not have come to completion without her encouragement and help. I want to also thank Sara Schumacher, VRA Bulletin Content Editor; it’s her initial invitation for this article that motivated me to write about this 18 month-long group project. Last but not least, I want to express my deep gratitude to the translation team. I thank the team for their input on the draft of this paper and also for their persistence in carrying out the translation project from beginning to end. 

Author Biography

Xiaoli Ma, University of Florida

Xiaoli Ma is the Metadata Librarian and the Head of Metadata Unit at the George A. Smathers Libraries, University of Florida. She develops metadata guidelines and implements workflows to enhance the usability and searchability of the content held by large-scale digital libraries. Currently, she explores the use of AI technology to automate the subject-indexing process. She studied Information Science, Art History, and American Literature at the University of Michigan, the University of South Florida, and Sichuan University, mainland China. Previously, she worked at Artstor as Metadata Specialist – Technical Lead, where she collaborated with developers and interface designers to create tools to collect, migrate, and update metadata.