The DBpedia Data Set

The DBpedia data set uses a large multi-domain ontology which has been derived from Wikipedia. The DBpedia data set currently describes 3.4 million “things” with over 1 billion “facts” (March 2010).

1. Background

Wikipedia has grown into one of the central knowledge sources of mankind and is maintained by thousands of contributors. Wikipedia articles consist mostly of free text, but also contain different types of structured information, such as infobox templates,categorisation information, images, geo-coordinates, and links to external Web pages. For instance, the figure below shows the source code and the visualisation of an infobox template containing structured information about the town of Innsbruck.

The DBpedia project extracts various kinds of structured information from Wikipedia editions in 92 languages and combines this information into a huge, cross-domain knowledge base.

DBpedia uses the Resource Description Framework (RDF) as a flexible data model for representing extracted information and for publishing it on the Web. We use the SPARQL query language to query this data. Please refer to the Developers Guide to Semantic Web Toolkits to find a development toolkit in your preferred programming language to process DBpedia data.

2. Content of the DBpedia Data Set

The DBpedia knowledge base currently describes more than 3.4 million things, out of which 1.5 million are classified in a consistent Ontology, including 312,000 persons, 413,000 places (including 310,000 populated places), 94,000 music albums, 49,000 films, 15,000 video games, 140,000 organizations (including 31,000 companies and 31,000 educational institutions), 146,000 species and 4,600 diseases. The DBpedia data set features labels and abstracts for these 3.2 million things in up to 92 different languages; 841,000 links to images and 5,081,000 links to external web pages; 9,393,000 external links into other RDF datasets, 565,000 Wikipedia categories, and 75,000 YAGO categories. The DBpedia knowledge base altogether consists of over 1 billion pieces of information (RDF triples) out of which 257 million were extracted from the English edition of Wikipedia and 766 million were extracted from other language editions.

The table below contains links to some example “things” from the data set:

Class	Examples
City	Cambridge, Berlin, Manchester
Country	Spain, Iceland, South Korea
Politician	George W. Bush, Nicolas Sarkozy, Angela Merkel
Musician	AC/DC, Diana Ross, Röyksopp
Music album	Led Zeppelin III, Like a Virgin, Thriller
Director	Woody Allen, Oliver Stone, Takashi Miike
Film	Pulp Fiction, Hysterical Blindness, Breakfast at Tiffany's
Book	The Lord of the Rings, The Adventures of Tom Sawyer, The Holy Bible
Computer Game	Tetris, World of Warcraft, Sam & Max hit the Road
Technical Standard	HTML, RDF, URI

You can also use Richard Cyganiak's PHP script to view random things from the DBpedia data set.

Find the properties used in the different DBpedia data sets here.

3. Identifying “things”

Each thing in the DBpedia data set is identified by a URI reference of the form http://dbpedia.org/resource/Name, where Name is taken from the URL of the source Wikipedia article, which has the form http://en.wikipedia.org/wiki/Name. Thus, each resource is tied directly to an English-language Wikipedia article.

4. Describing “things”

Each DBpedia resource is described by various properties. Below, we give an overview about the most important types of properties.

4.1. Basic Information

Every DBpedia resource is described by a label, a short and long English abstract, a link to the corresponding Wikipedia page, and a link to an image depicting the thing (if available).

If a thing exists in multiple language versions of Wikipedia, then short and long abstracts within these languages and links to the different language Wikipedia pages are added to the description. The DBpedia data set contains the following numbers of abstracts per language (March 2010):

4.2. Classifications

DBpedia provides three different classification schemata for things.

1. Wikipedia Categories are represented using the SKOS vocabulary.
2. The YAGO Classification is derived from the Wikipedia category system using Word Net. Please refer to Yago: A Core of Semantic Knowledge – Unifying WordNet and Wikipedia for more details.
3. Word Net Synset Links were generated by manually relating Wikipedia infobox templates and Word Net synsets, and adding a corresponding link to each thing that uses a specific template. In theory, this classification should be more precise then the Wikipedia category system.

Using these classifications within SPARQL queries allows you to select things of a certain type.

4.2.1. Wikipedia Categories

• NBA Teams (Does not work with Internet Explorer)
• Car manufacturers

4.2.2. YAGO Classes

• European Capitals
• Birds of the United States

4.2.3. Wordnet

• Software
• Airlines

4.3. Infobox Data

Wikipedia infoboxes contain very specific information about things and are thus a very valuable source of structured information that can be used to ask expressive queries against Wikipedia. The DBpedia project currently extracts three different datasets from the Wikipedia infoboxes.

1. The Infobox Dataset is created using our initial, now three year old infobox parsing approach. This extractor extracts all properties from all infoboxes and templates within all Wikipedia articles. Extracted information is represented using properties in the http://dbpedia.org/property/ namespace. The names of the these properties directly reflect the name of the Wikipedia infobox property. Property names are not cleaned or merged. Property types are not part of a subsumption hierarchy and there is no consistent ontology for the infobox dataset. Currently, there are approximately 8000 different property types. The infobox extractor performs only a minimal amount of property value clean-up, e.g., by converting a value like “June 2009” to the XML Schema format “2009–06”. You should therefore use the infobox dataset only if your application requires complete coverage of all Wikipeda properties and you are prepared to accept relatively noisy data.
2. The Infobox Ontology. With the DBpedia 3.2 release, we introduced a new infobox extraction method which is based on hand-generated mappings of Wikipedia infoboxes/templates to a newly created DBpedia ontology. The ontology consists of 259 classes which form a subsumption hierarchy and have altogether 1200 properties. The mappings adjust weaknesses in the Wikipedia infobox system, like using different infoboxes for the same type of thing (class) or using different property names for the same property. Therefore, the instance data within the infobox ontology is much cleaner and better structured than the Infobox Dataset, but currently doesn't cover all infobox types and infobox properties within Wikipedia. Starting with DBpedia release 3.5, we provide three different Infobox Ontology data sets:
   • The Ontology Infobox Types dataset contains the rdf:types of of the instances which have been extracted from the infoboxes.
   • The Ontology Infobox Properties dataset contains the actual data values that have been extracted from infoboxes. The data values are represented using ontology properties (e.g., 'volume') that may be applied to different things (e.g., the volume of a lake and the volume of a planet). This restricts the number of different properties to a minimum, but has the drawback that it is not possible to automatically infer the class of an entity based on a property. For instance, an application that discovers an entity described using the volume property cannot infer that that the entity is a lake and then for example use a map to visualize the entity. Properties are represented using properties following the http://dbpedia.org/ontology/{propertyname} naming schema. All values are normalized to their respective SI unit.
   • The Ontology Infobox Properties (Specific) dataset contains properties which have been specialized for a specific class using a specific unit. e.g. the property height is specialized on the class Person using the unit centimetres instead of metres. Specialized properties follow the http://dbpedia.org/ontology/{Class}/{property} naming schema (e.g. http://dbpedia.org/ontology/Person/height). The properties have a single class as rdfs:domain and rdfs:range and can therefore be used for classification reasoning. This makes it easier to express queries against the data, e.g., finding all lakes whose volume is in a certain range. Typically, the range of the properties are not using SI units, but a unit which is more appropriate in the specific domain.

All three data sets are available for download as well as being available for queries via the DBpedia SPARQL endpoint.

The infobox data enables sophisticated, fine-grained queries over the data set. Some example queries are shown below:

4.3.1. Querying the Infobox Dataset

• Abstracts of movies starring Tom Cruise, released before 1999
• The official websites of companies with more than 50000 employees
• Cities with more than 2 million habitants

4.3.2. Querying the Infobox Ontology

List all episodes of the HBO television series The Sopranos ordered by their air-date:

SELECT * WHERE { ?e <http://dbpedia.org/ontology/series> <http://dbpedia.org/resource/The_Sopranos> . ?e <http://dbpedia.org/ontology/releaseDate> ?date . ?e <http://dbpedia.org/ontology/episodeNumber> ?number . ?e <http://dbpedia.org/ontology/seasonNumber> ?season } ORDER BY DESC(?date)

SPARQL Result

Software developed by an organisation founded in California:

SELECT * WHERE { ?company a <http://dbpedia.org/ontology/Organisation> . ?company <http://dbpedia.org/ontology/foundationPlace> <http://dbpedia.org/resource/California> . ?product <http://dbpedia.org/ontology/developer> ?company . ?product a <http://dbpedia.org/ontology/Software> }

SPARQL Result

4.4. External Links

The DBpedia data set contains HTML links to external web pages as well as RDF links into external data sources.

There are two types of links to HTML pages: dbpedia:reference links point to several web pages about a thing. In addition, some things also have foaf:homepage links that point to web pages that can be considered the “official homepage” of a thing.

RDF links are represented using the owl:sameAs property. Please refer to Interlinking for more information about RDF links and the interlinked data sets.

4.4.1. FOAF Homepage

• Official websites of Universities
• Official websites of Capitals

4.4.2. Owl:sameAs Links

• Geographical (to GeoNames.org, Eurostat data, and the RDF version of the CIA Factbook):
  • Countries
• Authors / Books (to quotationsbook.com and Project Gutenberg RDF. Links to the RDF Book Mashup will follow soon ):
  • Authors
• Computer Scientist publications DBLP:
  • DBLP
• U.S. Census Statistical Data rdfabout.com, RDF version by Joshua Tauber:
  • Links for States of the U.S.A.

4.5. Geo-Coordinates

The DBpedia data set contains geo-coordinates for 392,000 geographic locations. Geo-coordinates are expressed using the W3C Basic Geo Vocabulary.

Besides simple listings of geo-coordinates (e.g., German soccer stadiums ), the new geo-coordinates allow sophisticated queries, like “show me all things next to the”:

• Eiffel Tower
• Brandenburg Gate

5. Provenance Meta-Data

In addition to the triples provided by the N-Triples datasets, the N-Quads datasets include a provenance URI to each statement. The provenance URI denotes the origin of the extracted triple in Wikipedia.

The provenance URI is composed of the URI of the article from Wikipedia where the statement has been extracted and a number of parameters denoting the exact source line.
The following parameters are set:

• absolute-line: The (absolute) line in the Wikipedia article source. The first line of a source has the line number 1.
• relative-line: The line in the Wikipedia article source in respect of the current section.
• section: The section inside the article

Example:
http://en.wikipedia.org/wiki/BMW_7_Series#section=E23&relative-line=1&absolute-line=23
The source of the given statement can be found in the 23th line. It is located in the first line of the section “E23”.

6. License

DBpedia is derived from Wikipedia and is distributed under the same licensing terms as Wikipedia itself. As Wikipedia has moved to dual-licensing, we also dual-license DBpedia starting with release 3.4.

DBpedia 3.4 data is licensed under the terms of the Creative Commons Attribution-ShareAlike 3.0 license and the GNU Free Documentation License. All DBpedia releases up to and including release 3.3 are licensed under the terms of the GNU Free Documentation License only.

This material is Open Knowledge.Cccc