Digital Technologies Expo
As information on Chinese books proliferates online, bibliographic descriptions of premodern Chinese works are increasingly easy to access, as are full digital transcriptions of many important texts. This digital information, while extensive, can sometimes be messy, ambiguously structured, and difficult to work with. In spite of this, it is possible to transform this information into clean, structured datasets that facilitate historical and literary analysis. In this talk, Paul Vierthaler will discuss a workflow for distilling messy information into usable data and present a number of ways to analyze and visualize bibliographic and textual data. Although Paul will briefly touch upon data preparation, this talk will primarily emphasize interactive visualization methods that aid data exploration and discovery using examples from his own research. Paul will show that by using flexible tools that allow filtering, panning, and zooming, scholars can more readily identify previously unnoticed trends in their data and use it to tell compelling stories about Chinese literary history.