addressing the cognitive difficulties of expressing n-ary relations in semantic web data
We present results from an empirical study in which everyday users attempted to generate formal knowledge representations for use in the Semantic Web. In particular, we focus on one especially difficult aspect of knowledge creation: statements that embody n-ary relations and therefore require reification of the verb in order to be expressible in standard RDF. In a cognitive experiment performed on over 80 novices, participants were asked to author statements containing n-ary relations corresponding to textual passages they were given. Our study compares the results between visual and text-based representations, illustrates the extent of the problem, and offers an alternative syntax for such relations that relieves several difficulties users face in properly formulating these statements. Our results soundly demonstrate that by allowing the use of this alternate syntax in place of traditional approaches, non-initiates can achieve much greater accuracy and coverage in the knowledge they generate. Further, knowledge modeled with the syntax can be trivially converted to standard RDF triples "behind" the user interface, so that the knowledge a user generates constitutes valid Linked Data.
semantic web linked data user interface design