An Open Platform for a Large, Multilingual, Semantic Knowledge Graph

The DBpedia project is aiming to extract structured content from the information created in various Wikimedia projects. This structured information resembles an open knowledge graph (KG) which is available for everyone on the Web. A knowledge graph is a special kind of database which stores knowledge in a machine-readable form and provides a means for information to be collected, organised, shared, searched and utilised. Google uses a similar approach to create those knowledge cards during search.

DBpedia currently describes 38.3 million “things” of 685 different “types” in 125 languages, with over 3 billion “facts” (September 2014). It is interlinked to many other databases (e.g., Wikidata, New York Times, CIA World Factbook). The knowledge in DBpedia is exposed through a set of technologies called Linked Data. Started in 2006, DBpedia is one of the first (if not THE first) open knowledge graph on the Web. DBpedia provides tools that allow you to create, maintain, improve, integrate and use KGs to build applications, e.g. BBC has created the World Cup 2010 website by interconnecting textual content and facts from their knowledge base. Data provided by DBpedia was greatly involved in creating this knowledge graph. More recently, IBM's Watson used DBpedia data to win the Jeopardy challenge. Several other large, medium and small companies use data from DBpedia everyday.

DBpedia data is served as Linked Data, which is revolutionizing the way applications interact with the Web. One can navigate this Web of facts with standard Web browsers, automated crawlers or pose complex queries with SQL-like query languages (e.g. SPARQL). Have you thought of asking the Web about all cities with low criminality, warm weather and open jobs? That's the kind of query we are talking about.

We are regularly growing our community through GSoC and can deliver more and more opportunities to you.

lightbulb_outline View ideas list


  • rdf
  • scala
  • sparql


comment IRC Channel
email Mailing list
mail_outline Contact email

DBpedia 2018 Projects

  • Aman Mehta
    A Neural QA Model for DBpedia
    Extending Neural SPARQL Machines (NSpM) to cover more DBpedia classes to enable high quality Question Answering
  • Bharat Suri
    Complex Embeddings for OOV Entities
    The aim of this project is to enhance the DBpedia Knowledge Base by enabling the model to learn from the corpus and generate embeddings for different...
  • Víctor Fernández
    Web application to detect incorrect mappings across DBpedias in different languages
    The DBpedia mappings for each language are not aligned, causing inconsistencies in the quality of the RDF generated. This is often a consequence of...