RcaDF: Towards a Relational Content Analysis Standard

Increasing numbers of high quality tools and data sets are becoming available for the study of media content, providing an opportunity for more rapid progress in Communication Science if these tools and data sets could be effectively combined and shared. In order to do so, it would be beneficial to have a shared Data format that is flexible enough to allow for changing research methods, expressive enough to deal with sophisticated content, yet has a clear semantic interpretation within and outside of the discipline. This paper proposes RcaDF, an expressive and flexible standard for Relational Content Analysis (Rca) based on the Resource Description Framework (RDF). Translations of existing data in NET, DyNETML, WorldView, and TABARI formats will be given, showing how data from these sources can be effectively combined, visualized, and analyzed. This standard will help researchers to share and combine data within and between institutions, to develop more general analysis and extraction tools, and to increase the usage of existing external repositories and tools.