Abstract
Knowledge acquisition is a central issue of the Semantic Web. Knowledge cannot always be automatically extracted from existing data, thus domain experts are required to manually produce it. On the one hand, learning formal languages such as RDF represents an important obstacle to non-IT experts. On the other hand, well-known data input interfaces do not address well the relational nature and flexibility of RDF. Furthermore, it is difficult to maintain data quality through time, and across contributors. We propose FORMULIS, a form-based interface for guided RDF authoring. It hides RDF notations, addresses the relational aspects with nested forms, and guides users by computing intelligent filling suggestions. Two user experiments show that FORMULIS helps users maintain good data quality, and can be used by users without Semantic Web knowledge.
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Available at http://servolis.irisa.fr:8080/formulis/.
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Acknowledgement
This work is supported by ANR project IDFRAud (ANR-14-CE28-0012). We thank our partners of project IDFRAud, as well as the experts from IRCGN and the fourteen volunteers who participated in our experiments.
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Maillot, P., Ferré, S., Cellier, P., Ducassé, M., Partouche, F. (2017). Nested Forms with Dynamic Suggestions for Quality RDF Authoring. In: Benslimane, D., Damiani, E., Grosky, W., Hameurlain, A., Sheth, A., Wagner, R. (eds) Database and Expert Systems Applications. DEXA 2017. Lecture Notes in Computer Science(), vol 10438. Springer, Cham. https://doi.org/10.1007/978-3-319-64468-4_3
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