The Visual Resources Association (VRA) is pleased to announce that Chinese translations of VRA Core 4.0 are now available on the Library of Congress VRA Core page. The VRA Core is a data standard for the description of works of visual culture as well as the images that document them.
Members of the VRA’s Cataloging and Metadata Standards Committee (CaMS) led and assisted on the project along with a group of five library professionals from American institutions. This team began the project to translate the VRA Core 4.0 Element Description into traditional and simplified Chinese in January 2021. The translation project went through multiple revisions before bilingual scholars and practitioners in the U.S., Taiwan, and P.R. China with years of experience with cultural heritage metadata were invited to review the drafts.
In response to reviewers’ suggestions on the translation and formatting, the group carried through more rounds of modification and presented drafts for public comment in June 2022. The final translations now available on the VRA Core website incorporate feedback received during these multiple rounds of revision.
The VRA Board and the Chair of the CaMS, Leah Constantine, would like to congratulate the following participants and thank them for their dedicated work on this project!
Project Lead: Xiaoli Ma, George A. Smathers Libraries, University of Florida
DTP: K. Sarah Ostrach, Hoover Institution Library & Archives, Stanford University
Translators: Ching-jung Chen, The City College of the City University of New York Libraries; Sai Deng, University of Central Florida Libraries; Xiaoli Ma, George A. Smathers Libraries, University of Florida; Jane Pen, George A. Smathers Libraries, University of Florida;
Reviewers: Sophy Shu-Jiun Chen, Institute of History and Philology, Academia Sinica, Taiwan; Charlene Chou, New York University Library; Fan Wei, Sichuan University, P. R. China; Carol Ng-He, Center for the Art of East Asia, The University of Chicago; Shu-Wen Lin, San Francisco Museum of Modern Art; Marcia Lei Zeng, School of Information, Kent State University
