Our paper on "Enabling Structured Data Generation by Non-Technical Experts" (Andre Breitenfeld, Maximilian Mackeprang, Ming-Tung Hong, Claudia Müller-Birn) was accepted for presentation at the "Mensch & Computer 2017" conference.

Abstract: The Semantic Web provides meaning to information resources in the form of machine-accessible structured data. Research in the Semantic Web field commonly focused on tools and inter- faces for technical experts leading to various usability problems in the field. The complexity of Semantic Web technology makes it difficult especially for non-technical experts to use these technologies. Existing research on Semantic Web usability considers mostly consumers of structured data that leave out the creation perspective. In this work, we focus on the usability of creating structured data from text, especially on the creation of relations between entities. We reviewed existing research and state of the art annotation tools to establish shortcomings and used our knowledge to propose an interaction design for the creation of relations. A user a study that we conducted showed that the proposed interaction design performed well, making it a contribution to enhance the overall usability in the field.