A drag-and-block approach for linked open data exploration
Tuan-Dat Trinh, Ba-Lam Do, Peter Wetz, Amin Anjomshoaa, Elmar Kiesling, A Min Tjoa · 2014
Abstract. Since its initial definition in 2007, the concept of Linked Open Data (LOD) has gained strong traction in the scientific commu-nity. However, mainstream adoption has been limited and the emergence of an envisioned global linked data space is still in its early stages. One possible explanation is the gap between the large amounts of published LOD datasets and the lack of end-user tools to effectively explore them. Because existing applications are tailored towards specific datasets and do not allow for reuse and extension, novice users have so far had lim-ited means to access the rich data sources being published. To address this issue, we introduce a novel approach to support non-expert users in the flexible exploration of LOD. To this end, we define a formal model that makes use of existing links between interconnected datasets. We im-plement the model in a mashup platform and illustrate its potential by means of use cases combining Open Data and Linked Open Data sources. 1