The project aims to create a research database on Japanese visual media, including, but not limited to anime, manga, computer games and visual novels. It is aimed at researchers in Japan studies who focus on modern media and its expressions, themes, topics, characters and reception. We envision a graph-based, highly interconnected database structure, similar to the Google knowledge graph, that is combined with a flexible search interface and analytic tools.
We intend to use the data on Japanese visual media that is being created and curated by the many enthusiast communities on the web. An initial survey of several larger community websites showed an incredible depth of information, a deep understanding of the source material as well as a high attention to details on part of the volunteer contributors. As such, making contact with these communities and learning about their needs and motivations is one of the main project elements. We intend to engage into a meaningful discussion with representatives and administrators of the community sites in order to establish a long-term cooperation that benefits both sides.
The architecture will be completely open source and most likely be based on the software stack that is being developed in the Wikidata project. It is one of the more advanced deployment of a huge graph-based database with integrated search and visualization features and has an already established development community. It also provides means to annotate and propose changes to the data in a well-documented and traceable way.
The whole development phase will be accompanied by researchers from the Japan Studies, who will be responsible for data selection as well as data quality assurance. They will make sure that both the data model and the architecture of the prototype supports their research by conducting example research and verifying the results. Once a first prototype has been developed to the satisfaction of the project partners, it will be made accessible to the larger Japanese media studies research community as well as other researchers who are interested in the data harvesting and modelling aspects.