The Academia Sinica Digital Analysis System for Humanities offers itself as a digital environment to advance scholarship that involves the analysis of Chinese scripts in making use of computational techiniques.
Since its inception two years ago, this platform distills the work of the Academia Sinica Center for Digital Cultures (ASCDC) to enhance the quality of scholarship in the humanities. It is now open to users around the world.
Viewing that research platform has become an important terrain productively appropirated by the digital humanities, ASCDC has built a cyberinfrastructure in support of the burgeoning in both local and global contexts. Zeroing on textual analysis as the core work of many scholars in the humanities, this platform applies big data analysis to reading and suggests hitherto underexamined areas illuminated by the affordances of computer.
To achieve this, the platform provides a rich seam of materials, tools, and co-working network. Its cloud-based operation allows for open access and collaborative editing. You can not only upload your own texts and authority files but also freely join research groups sharing the same interest. This platform possesses an open-ended corpus that grows in time, available for automatic markup, frequency analysis, text comparison, associative analysis, spatial-temporal presentation, and data visualization.
So far, the platform contains Chinese texts imported by the Scripta Sinica database of Academia Sinica, Kanripo of Kyoto University, Ctext of Harvard University, amounting to a total of 8 billion characters. The authority files contain the place names of China Historical Geographic Information System (CHGIS), the names of China Biographical Database (CBDB), and so on. This forms a strong basis for textual query, which can operate with hierarchical structures that sort the authority files into categories and texts into paragraph, chapter, book or volume.
It is commonplace today to perceive the digital humanities as a site that generates revolutionary paradigms for scholarship. The networking service provided by the Academia Sinica Digital Analysis System for Humanities aims to build on this potential by integrating scholarly work in the humanities that goes beyond individual endeavor.
ASCDC is currently working on introducing the structure of Linked Open Data (LOD), International Image Interoperability Framework (IIIF), optical character recognition (OCR), and named entity recognition (NER) in order to amplify and upgrade the analytical capacity of this platform.
