
The wide adaptation of the Semantic Web and the Resource Description Framework (RDF) has made available many important datasets. The SPARQL query language facilitates the exploration of this information, which is available in a semi-structured way that does not comply with relational data models, deviating from exploration techniques that most researchers are familiar with. Usually, only people with training and extensive knowledge of the RDF model can explore and understand it in depth. We present here a platform that supports the users with querying, exploring and visualizing information available in SPARQL endpoints. A dedicated visualization module, built upon a knowledge database, allows us to provide case-specific visualization solutions for SPARQL query results. The selection is based exclusively on features extracted from the result, without any knowledge about the structure, content and characteristics of the underlying dataset.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 2 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
