Name
Abstract | ||
|---|---|---|
Linked Data sets are an ever-growing, invaluable source of information and knowledge. However, the wide adoption of this large amount of interlinked structured data is still held back by some nontrivial obstacles. The one we tackle in this article is the difficulty users have in getting started with their work on Linked Data sources. In fact, querying, and in general dealing with such datasets, requires a deep knowledge about their specific classes, instances and properties. We believe that an entry point that eases the access to such information would significantly reduce the barriers around this technology and foster its promotion. Linked Data Maps is a method for representing RDF graphs as interactive, map-like visualizations, based on our previous work focused on the visual exploration of DBpedia. The approach is extended to deal with a wider range of Linked Data sets, and tested with a user evaluation study on two distinct RDF graphs. |
Year | Venue | Field |
|---|---|---|
2015 | IESD@ISWC | Data science,Information retrieval,Entry point,Linked data,Geography,Data model,Rdf graph,Deep knowledge |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
18 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fabio Valsecchi | 1 | 6 | 1.44 |
| Matteo Abrate | 2 | 14 | 4.17 |
| Clara Bacciu | 3 | 16 | 3.64 |
| Maurizio Tesconi | 4 | 281 | 32.06 |
| Andrea Marchetti | 5 | 3 | 1.04 |