Enabling Structured Data Generation by Nontechnical Experts
dc.contributor.author | Breitenfeld, Andre | |
dc.contributor.author | Mackeprang, Maximilian | |
dc.contributor.author | Hong, Ming-Tung | |
dc.contributor.author | Müller-Birn, Claudia | |
dc.contributor.editor | Burghardt, Manuel | |
dc.contributor.editor | Wimmer, Raphael | |
dc.contributor.editor | Wolff, Christian | |
dc.contributor.editor | Womser-Hacker, Christa | |
dc.date.accessioned | 2017-08-09T21:05:07Z | |
dc.date.available | 2017-08-09T21:05:07Z | |
dc.date.issued | 2017 | |
dc.description.abstract | The Semantic Web provides meaning to information resources in the form of machine-accessible structured data. Research in the Semantic Web field focuses commonly on tools and interfaces for technical experts leading to various usability problems. The complexity of Semantic Web technology makes it difficult especially for nontechnical 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. We conducted a user-study which showed that the proposed interaction design performed well, making it a contribution to enhance the overall usability in the field. | en |
dc.identifier.doi | 10.18420/muc2017-mci-0231 | |
dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/3264 | |
dc.language.iso | en | |
dc.publisher | Gesellschaft für Informatik e.V. | |
dc.relation.ispartof | Mensch und Computer 2017 - Tagungsband | |
dc.relation.ispartofseries | Mensch und Computer | |
dc.subject | semantic annotation | |
dc.subject | usability | |
dc.subject | semantic relations | |
dc.subject | interaction-design | |
dc.title | Enabling Structured Data Generation by Nontechnical Experts | en |
dc.type | Text/Conference Paper | |
gi.citation.endPage | 192 | |
gi.citation.publisherPlace | Regensburg | |
gi.citation.startPage | 181 | |
gi.conference.date | 10.-13. September 2017 | |
gi.conference.location | Regensburg | |
gi.conference.sessiontitle | Tools: Design und Evaluation | |
gi.document.quality | digidoc |
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