Research any topic before you write.
Find related topics. | Discover entities. | See connections. | Build a topical map.
DBpedia (from "DB" for "database") is a project aiming to extract structured content from the information created in the Wikipedia project. This structured information is made available on the World Wide Web using OpenLink Virtuoso. DBpedia allows users to semantically query relationships and properties of Wikipedia resources, including links to other…
History & Applications
Explore the main themes, entities and connections around DBpedia. Start with the topic map, then use the sections below for research and deeper semantic analysis.
Start with a few of the strongest sections from the source topic. These are research directions, not a list of keywords you must use.
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Browse the full topic structure. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
See the strongest relationship patterns around the current topic before diving into the raw triples.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
data information web wikipedia project also database spotlight structured use semantic datasets extracted available one million dataset links linked ontology
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| DBpedia | Developers | Leipzig University | 1.00 | infobox |
| DBpedia | Developers | University of Mannheim | 1.00 | infobox |
| DBpedia | License | GNU General Public License | 1.00 | infobox |
| DBpedia | Release | 10 January 2007 (19 years ago) (2007-01-10) | 1.00 | infobox |
| DBpedia | Repository | github.com/dbpedia/ | 1.00 | infobox |
| DBpedia | Stable release | DBpedia 2016-10 / 4 July 2017 | 1.00 | infobox |
| DBpedia | Type | Semantic Web | 1.00 | infobox |
| DBpedia | Type | linked data | 1.00 | infobox |
| DBpedia | Website | dbpedia.org | 1.00 | infobox |
| DBpedia | Written in | Scala | 1.00 | infobox |
| DBpedia | Written in | Java | 1.00 | infobox |
| Super Doll Licca-chan | instance of | Mia Ikumi and on this author's works | 0.80 | text |
These clusters group vocabulary that occurs around closely connected concepts in the source material.
Bridges can reveal useful research angles that are easy to miss in a flat list of related terms.