Since 2017, the Network Institute has proudly been a member of the DBpedia Association, contributing to one of the most impactful projects in the Linked Open Data ecosystem. This partnership reflects our commitment to open knowledge, data sharing, and supporting new ways of research, and innovation through the smart use of data.
What is DBpedia’s mission?
Founded in 2007 through a collaboration between the Free University of Berlin, Leipzig University, and OpenLink Software, DBpedia is now actively maintained by researchers at Leipzig University and the University of Mannheim. The project has since grown into one of the foundational pillars of the Linked Open Data (LOD) cloud and has played a critical role in shaping the Semantic Web. The data is made available under Creative Commons Attribution-ShareAlike (CC BY-SA) licenses, allowing widespread reuse while preserving attribution requirements.
Wikipedia articles consist mostly of free text, but also include structured information embedded in the articles, such as “infobox” tables, categorization information, and links to external Web pages. This structured information is extracted by DBpedia and put in a uniform datasets which can then be queried. [1]
By enabling the semantic querying of relationships and attributes associated with Wikipedia resources, developers, data scientists, and researchers are faciliated in building intelligent applications, knowledge graphs, and data integration tools across a wide range of disciplines. These structured datasets serve as the backbone for many applications in fields such as artificial intelligence, digital humanities, media analytics, and cultural heritage.
Tim Berners-Lee, inventor of the World Wide Web, once described DBpedia as “one of the more famous pieces” of the decentralized Linked Data effort, highlighting its impact on the evolution of open, connected data infrastructures.
As of June 2021, the DBpedia dataset includes over 6 million structured entities, including:
- 1.5 million people.
- More than 850 million RDF triples representing extracted knowledge.
- Data spanning over 20 Wikipedia language editions.
🔍 DBpedia Spotlight
One of the standout tools in the ecosystem is DBpedia Spotlight, which enables semantic annotation of text by recognizing and linking entities to DBpedia resources. This allows developers and researchers to:
- Detect and disambiguate named entities
- Link unstructured text to Linked Open Data
- Enhance information retrieval and knowledge discovery
With multilingual support and flexible APIs, DBpedia Spotlight is widely used in natural language processing, information extraction, and content analysis workflows.
[1] “DBpedia.” Wikipedia, Wikimedia Foundation, https://en.wikipedia.org/wiki/DBpedia.
