|Visual Language Research Corpus (VLRC)
How do the drawing systems and sequential images of cultures around the world differ? Do these differences tie into deeper aspects of cognition? Is there systematicity underlying the diversity of structures in these different visual languages? Answering these questions is a fundamental part of the study of visual language. To do this, we have engaged in an ongoing corpus analysis of comics from around the world.
The Visual Language Research Corpus (VLRC) is a database of coded comics (and, potentially, other visual media) used to investigate the structures in visual languages of the world. This research follows individual corpus studies on select fields of visual language structure. In 2013, we began a larger ongoing effort to design a growing database aimed at providing a resource for our own studies and other researchers.
At present, the VLRC is made up of 20,000 coded panels from roughly 200 comics from several places (America, France, Germany, Hong Kong, Japan, Korea), different time periods (1940-present), and various genres. It includes coding of panel framing, semantic relations between panels, external compositional structure (page layout), multimodality, and a variety of other structures of visual languages.
It is our intention to make the VLRC accessible to other researchers at this web-address via a searchable interface. Design and testing of this database is currently underway, along with documentation.
Several publishers have contributed to this research by generously donating comics to our growing corpus of research materials. They include:
Dark Horse Comics,
Drawn & Quarterly,
First Second Books,
Their support is greatly appreciated! If you or your company would like to donate materials to our research libarary, please contact me. International comics especially can help support our projects looking at cross-cultural comparisons. Publishers will be thanked in the acknowledgements of all papers that uses their resources, and any data culled will be provided upon request.
The data in the VLRC was coded by several student researchers. The include:
Ryan Huffman, Kaitlin Pederson, Ryan Taylor, Vivian Wong
The VLRC database itself was designed by Barak Tzori.