Matches in Ruben’s data for { ?s ?p "Semantically annotating and interlinking Open Data results in Linked Open Data which concisely and unambiguously describes a knowledge domain. However, the uptake of the Linked Data depends on its usefulness to non-Semantic Web experts. Failing to support data consumers understanding the added-value of Linked Data and possible exploitation opportunities could inhibit its diffusion. In this paper, we propose an interactive visual workflow for discovering and exploring Linked Open Data. We implemented the workflow considering academic library metadata and carried out a qualitative evaluation. We assessed the workflow’s potential impact on data consumers which bridges the offer as published Linked Open Data, and the demand as requests for: (i) higher quality data; and (ii) more applications that re-use data. More than 70% of the test users agreed that the workflow fulfills its goal: it facilitates non-Semantic Web experts to understand the potential of Linked Open Data."@en }
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- publication abstract "Semantically annotating and interlinking Open Data results in Linked Open Data which concisely and unambiguously describes a knowledge domain. However, the uptake of the Linked Data depends on its usefulness to non-Semantic Web experts. Failing to support data consumers understanding the added-value of Linked Data and possible exploitation opportunities could inhibit its diffusion. In this paper, we propose an interactive visual workflow for discovering and exploring Linked Open Data. We implemented the workflow considering academic library metadata and carried out a qualitative evaluation. We assessed the workflow’s potential impact on data consumers which bridges the offer as published Linked Open Data, and the demand as requests for: (i) higher quality data; and (ii) more applications that re-use data. More than 70% of the test users agreed that the workflow fulfills its goal: it facilitates non-Semantic Web experts to understand the potential of Linked Open Data.".