China and Inner Asia
In July 2018, the East Asian Library (EAL) of the University of Pittsburgh Library System (ULS) initiated the Contemporary Chinese Village Data (CCVD) project to create an open-access online dataset of statistics selected from the library’s collection of Chinese village gazetteers. This unique initiative has produced a dataset of significant value to the humanities and social sciences based on Chinese village gazetteers, which include quantitative and qualitative data critical to supporting Chinese studies in fields such as politics, economics, sociology, environmental science, history, and public health. Beginning in January 2020, a dataset including statistics from 1,000 villages will be available for download via the ULS digital collections website; over the next two years 1,500 to 2,000 villages will be added to the dataset. In this roundtable discussion, University Librarian and Head of the ULS, Dr. Kornelia Tancheva, will officially announce the dataset’s availability and describe its content and creation. The announcement of the CCVD dataset’s opening provides an opportunity for dialogue concerning future directions for scholar-librarian collaboration in Digital Humanities (DH). What kinds of DH projects can libraries initiate to support teaching and research? How can scholars and librarians collaborate on DH initiatives? What challenges do both sides face, and what are some ways to surmount such challenges? What do scholars expect from academic libraries in the digital era? Dr. Thomas Rawski (University of Pittsburgh), an expert on Chinese economics; Dr. Pierre Landry (Chinese University of Hong Kong), an expert on Chinese Government and Administration; Dr. Huaiyin Li (University of Texas, Austin), a scholar on Chinese history; and Dr. Minhua Ling and Dr. Yu Xiao, junior scholars will discuss research using CCVD data from the dataset’s initial soft opening in fall 2019. In their conversation, the chair and discussants will share their experiences collaborating on DH projects within academic libraries, and utilizing the products of DH initiatives in their research. They will comment on areas for improvement in both the CCVD dataset and other digital projects, and share their thoughts on future DH initiatives according to their own fields of study, research methods, and experience in academia.