Note We are moving the content of this website to our new page currently located here, we will switch within the next days (written 29th of Aprli)



DBpedia is a crowd-sourced community effort to extract structured information from Wikipedia and make this information available on the Web. DBpedia allows you to ask sophisticated queries against Wikipedia, and to link the different data sets on the Web to Wikipedia data. We hope that this work will make it easier for the huge amount of information in Wikipedia to be used in some new interesting ways. Furthermore, it might inspire new mechanisms for navigating, linking, and improving the encyclopedia itself.


Wiki Contents

This Wiki provides information about the DBpedia community project:

  • Datasets gives an overview about the DBpedia knowledge base.
  • Ontology gives an overview about the DBpedia ontology.
  • Online Access describes how the data set can be accessed via a SPARQL endpoint and as Linked Data.
  • Downloads provides the DBpedia data sets for download.
  • Interlinking describes how the DBpedia data set is interlinked with various other datasets on the Web.
  • Use Cases lists different use cases for the DBpedia data set.
  • Extraction Framework describes the DBpedia information extraction framework.
  • Data Provision Architecture paints a picture of the software and protocols used to serve DBpedia on the Web.
  • Community explains how the DBpedia community collaborates and how people can contribute to the DBpedia effort.
  • DBpedia Mapping Wiki containing the mappings used by the DBpedia extraction.
  • DBpedia Internationalization Effort working towards providing multiple language-specific versions of DBpedia.
  • DBpedia-Live presents the new DBpedia-Live framework.
  • DBpedia Spotlight presents the DBpedia Spotlight tool for the semantic annotation of textual content.
  • Credits lists the people and institutions that have contributed to DBpedia so far.
  • Change Log lists the DBpedia releases and gives an overview about the changes for earch release.
  • Next steps describes ideas and future plans for the DBpedia project.

The DBpedia Knowledge Base

Knowledge bases are playing an increasingly important role in enhancing the intelligence of Web and enterprise search and in supporting information integration. Today, most knowledge bases cover only specific domains, are created by relatively small groups of knowledge engineers, and are very cost intensive to keep up-to-date as domains change. At the same time, Wikipedia has grown into one of the central knowledge sources of mankind, maintained by thousands of contributors.


The DBpedia project leverages this gigantic source of knowledge by extracting structured information from Wikipedia and by making this information accessible on the Web under the terms of the Creative Commons Attribution-ShareAlike 3.0 License and the GNU Free Documentation License.



The English version of the DBpedia knowledge base describes 4.58 million things, out of which 4.22 million are classified in a consistent ontology, including 1,445,000 persons, 735,000 places (including 478,000 populated places), 411,000 creative works (including 123,000 music albums, 87,000 films and 19,000 video games), 241,000 organizations (including 58,000 companies and 49,000 educational institutions), 251,000 species and 6,000 diseases.


In addition, we provide localized versions of DBpedia in 125 languages. All these versions together describe 38.3 million things, out of which 23.8 million are localized descriptions of things that also exist in the English version of DBpedia. The full DBpedia data set features 38 million labels and abstracts in 125 different languages, 25.2 million links to images and 29.8 million links to external web pages; 80.9 million links to Wikipedia categories, and 41.2 million links to YAGO categories. DBpedia is connected with other Linked Datasets by around 50 million RDF links. Altogether the DBpedia 2014 release consists of 3 billion pieces of information (RDF triples) out of which 580 million were extracted from the English edition of Wikipedia, 2.46 billion were extracted from other language editions. Detailed statistics about the DBpedia datasets in 24 popular languages are provided at Dataset Statistics.


The DBpedia knowledge base has several advantages over existing knowledge bases: it covers many domains; it represents real community agreement; it automatically evolves as Wikipedia changes, and it is truly multilingual. The DBpedia knowledge base allows you to ask quite surprising queries against Wikipedia, for instance “Give me all cities in New Jersey with more than 10,000 inhabitants” or “Give me all Italian musicians from the 18th century”. Altogether, the use cases of the DBpedia knowledge base are widespread and range from enterprise knowledge management, over Web search to revolutionizing Wikipedia search.

Nucleus for the Web of Data

Within the W3C Linking Open Data (LOD) community effort, an increasing number of data providers have started to publish and interlink data on the Web according to Tim Berners-Lee’s Linked Data principles. The resulting Web of Data currently consists of several billion RDF triples and covers domains such as geographic information, people, companies, online communities, films, music, books and scientific publications. In addition to publishing and interlinking datasets, there is also ongoing work on Linked Data browsers, Linked Data crawlers, Web of Data search engines and other applications that consume Linked Data from the Web.


The DBpedia knowledge base is served as Linked Data on the Web. As DBpedia defines Linked Data URIs for millions of concepts, various data providers have started to set RDF links from their data sets to DBpedia, making DBpedia one of the central interlinking-hubs of the emerging Web of Data.


Feed Title: News (last 3 items)

Galway is calling for the next DBpedia Community Meeting.

We are happy to announce that the 9th DBpedia Community meeting will be held in Galway, Ireland on June 21st 2017. DBpedia will be part of the Language, Data and Knowledge conference (LDK) in Galway. This new biennial conference series aims at bringing together researchers from across disciplines. The DBpedia Meeting is part of the conference and is scheduled for the last day.

Only few seats are left: So come and get your ticket to be part of the 9th DBpedia Community meeting in Galway.

Highlights

  • Keynote #1: Logainm.ie data use cases by Brian Ó Raghallaigh (Dublin City University & Logainm)
  • Keynote #2: Wikimedia in Ireland: A Monumental Undertaking by Sharon Flynn (NUI Galway & Wikimedia Ireland)
  • DBpedia Association hour
  • A session about Irish Linked data projects (and DBpedia)

Quick Facts

Schedule

Please check our schedule for the 9th DBpedia Community meeting here: http://wiki.dbpedia.org/meetings/Galway2017

Evening Event

The social event will be held in the evening (starting at 6pm) at the PorterShed around the topic How to exploit data commercially? featuring several short impulse talks. We still have some remaining slots and would welcome you to present your success stories as well as use cases, but also tell us about your problems regarding the commercialisation of data. If you are interested in presenting, please email dbpedia@infai.org.

Sponsors and Acknowledgments

LDK2017 For hosting the meeting.
Institute for Applied Informatics For supporting the DBpedia Association.
OpenLink Software For continuous hosting of the main DBpedia Endpoint.
ADAPT research centre For supporting the DBpedia Association.
ALIGNED – Software and Data Engineering For funding the development of DBpedia as a project use-case and covering part of the travel cost.
PorterShed For hosting the evening event.

In case you want to sponsor the 9th DBpedia Community Meeting, please contact the DBpedia Association via dbpedia@infai.org.

Organisation

  • Tatiana Gornostay, TILDE
  • Rob Brennan, ADAPT research centre
  • Felix Sasaki, DFKI GmbH
  • Bianca Pereira, The Insight Centre for Data Analytics
  • Caoilfhionn Lane, The Insight Centre for Data Analytics
  • Jimmy O’Regan, ITUT, Trinity College Dublin
  • Julia Holze, DBpedia Association
  • Sandra Prätor, DBpedia Association
  • Sebastian Hellmann, DBpedia Association and AKSW, Uni Leipzig

We are looking forward to meeting you in Galway!

Check our website for further updates, follow us on #twitter or subscribe to our newsletter.

Your DBpedia Association

Smart Minds Wanted

New Internship Opportunity @

In conjunction with Springer Nature,  DBpedia offers a 3 months internship at Springer Nature in London, UK and at DBpedia in Leipzig, Germany.

Internship Details

Position DBpedia Intern
Main Employer DBpedia Association
Deadline June 30th, 2017
Duration 3 months/full-time, internship will starts in the second half of 2017
Location 50% in London (UK) and 50% in Leipzig (GER)
Type of students desired Undergraduate, Graduate (Junior role)
Compensation You will receive a stipend of 1300€ per month and additional reimbursement of your travel and visa costs (total up to 1000€)

The student intern will be responsible for assisting with mappings for DBpedia at SpringerNature. Your tasks include and are not restricted to improving the quality of the extraction mechanism of DBpedia scholarly references/wikipedia citations to Springer Nature URIs and Text mining of DBpedia entities from Springer Nature publication content.

Did we spark your interest? Check  our website for further information or apply directly via our online application form

We are looking forward to meet all the whiz kids out there.

Your

DBpedia Association

GSoC 2017- may the code be with you

GSoC students have finally been selected.

We are very excited to announce this year’s final students for our projects  at the Google Summer of Code program (GSoC).

Google Summer of Code is a global program focused on bringing more student developers into open source software development. Stipends are awarded to students to work on a specific DBpedia related project together with a set of dedicated mentors during summer 2017 for the duration of three months.

For the past 5 years DBpedia has been a vital part of the GSoC program. Since the very first time many Dbpedia projects have been successfully completed.

In this years GSoC edition, DBpedia received more than 20 submissions for selected DBpedia projects. Our mentors read many promising proposals, evaluated them and now the crême de la crême of students snatched a spot for this summer.  In the end 7 students from around the world were selected and will jointly work together with their assigned mentors on their projects. DBpedia developers and mentors are really excited about this 7 promising student projects.

List of students and projects:

You want to read more about their specific projects? Just click below… or check GSoC pages for details.[expander_maker id=”1″ more=”Read more” less=”Read less”] Ismael Rodriguez – Project Description: Although the DBPedia Extraction Framework was adapted to support RML mappings thanks to a project of last year GSoC, the user interface to create mappings is still done by a MediaWiki installation, not supporting RML mappings and needing expertise on Semantic Web. The goal of the project is to create a front-end application that provides a user-friendly interface so the DBPedia community can easily view, create and administrate DBPedia mapping rules using RML. Moreover, it should also facilitate data transformations and overall DBPedia dataset generation. Mentors: Anastasia Dimou, Dimitris Kontokostas, Wouter Maroy 

Ram Ganesan Athreya – Project Description:The requirement of the project is to build a conversational Chatbot for DBpedia which would be deployed in at least two social networks.There are three main challenges in this task. First is understanding the query presented by the user, second is fetching relevant information based on the query through DBpedia and finally tailoring the responses based on the standards of each platform and developing subsequent user interactions with the Chatbot.Based on my understanding, the process of understanding the query would be undertaken by one of the mentioned QA Systems (HAWK, QANARY, openQA). Based on the response from these systems we need to query the DBpedia dataset using SPARQL and present the data back to the user in a meaningful way. Ideally, both the presentation and interaction flow needs to be tailored for the individual social network.I would like to stress that although the primary medium of interaction is text, platforms such as Facebook insist that a proper mix between chat and interactive elements such as images, buttons etc would lead to better user engagement. So I would like to incorporate these elements as part of my proposal.

Mentor: Ricardo Usbeck

 

Nausheen Fatma – Project discription:  Knowledge base embeddings has been an active area of research. In recent years a lot of research work such as TransE, TransR, RESCAL, SSP, etc. has been done to get knowledge base embeddings. However none of these approaches have used DBpedia to validate their approach. In this project, I want to achieve the following tasks: i) Run the existing techniques for KB embeddings for standard datasets. ii) Create an equivalent standard dataset from DBpedia for evaluations. iii) Evaluate across domains. iv) Compare and Analyse the performance and consistency of various approaches for DBpedia dataset along with other standard datasets. v)Report any challenges that may come across implementing the approaches for DBpedia. Along the way, I would also try my best to come up with any new research approach for the problem.

Mentors: Sandro Athaide Coelho, Tommaso Soru

 

Akshay Jagatap – Project Description: The project aims at defining embeddings to represent classes, instances and properties. Such a model tries to quantify semantic similarity as a measure of distance in the vector space of the embeddings. I believe this can be done by implementing Random Vector Accumulators with additional features in order to better encode the semantic information held by the Wikipedia corpus and DBpedia graphs.

Mentors: Pablo Mendes, Sandro Athaide Coelho, Tommaso Soru

 

Luca Virgili –  Project Description: In Wikipedia a lot of data are hidden in tables. What we want to do is to read correctly all tables in a page. First of all, we need a tool that can allow us to capture the tables represented in a Wikipedia page. After that, we have to understand what we read previously. Both these operations seem easy to make, but there are many problems that could arise. The main issue that we have to solve is due to how people build table. Everyone has a particular style for representing information, so in some table we can read something that doesn’t appear in another structure. In this paper I propose to improve the last year’s project and to create a general way for reading data from Wikipedia tables. I want to review the parser for Wikipedia pages for trying to understand more types of tables possible. Furthermore, I’d like to build an algorithm that can compare the column’s elements (that have been read previously by the parser) to an ontology so it could realize how the user wrote the information. In this way we can define only few mapping rules, and we can make a more generalized software.

Mentors: Emanuele Storti, Domenico Potena

 

Shashank Motepalli – Project Description: DBpedia tries to extract structured information from Wikipedia and make information available on the Web. In this way, the DBpedia project develops a gigantic source of knowledge. However, the current system for building DBpedia Ontology relies on Infobox extraction. Infoboxes, being human curated, limit the coverage of DBpedia. This occurs either due to lack of Infoboxes in some pages or over-specific or very general taxonomies. These factors have motivated the need for DBTax.DBTax follows an unsupervised approach to learning taxonomy from the Wikipedia category system. It applies several inter-disciplinary NLP techniques to assign types to DBpedia entities. The primary goal of the project is to streamline and improve the approach which was proposed. As a result, making it easy to run on a new DBpedia release. In addition to this, also to work on learning taxonomy of DBTax to other Wikipedia languages.

Mentors: Marco Fossati, Dimitris Kontokostas

 

Krishanu Konar – Project Description: Wikipedia, being the world’s largest encyclopedia, has humongous amount of information present in form of text. While key facts and figures are encapsulated in the resource’s infobox, and some detailed statistics are present in the form of tables, but there’s also a lot of data present in form of lists which are quite unstructured and hence its difficult to form into a semantic relationship. The project focuses on the extraction of relevant but hidden data which lies inside lists in Wikipedia pages. The main objective of the project would be to create a tool that can extract information from wikipedia lists, form appropriate RDF triplets that can be inserted in the DBpedia dataset.

Mentor: Marco Fossati [/expander_maker]

Congrats to all selected students! We will keep our fingers crossed now and patiently wait until early September, when final project results are published.

An encouraging note to the less successful students.

The competition for GSoC slots is always on a very high level and DBpedia only has a limited amount of slots available for students.  In case you weren’t among the selected, do not give up on DBpedia just yet. There are plenty of opportunities to prove your abilities and be part of the DBpedia experience. You, above all, know DBpedia by heart. Hence, contributing to our support system is not only a great way to be part of the DBpedia community but also an opportunity to be vital to DBpedia’s development. Above all, it is a chance for current DBpedia mentors to get to know you better. It will give your future mentors a chance to  support you and help you to develop your ideas from the very beginning.

Go on you smart brains, dare to become a top DBpedia expert and provide good support for other DBpedia Users. Sign up to our support page  or check out the following ways to contribute:

Get involved:
  • Join our DBpedia-discussion -mailinglist, where we discuss current DBpedia developments. NOTE: all mails announcing tools or call to papers unrelated to DBpedia are not allowed. This is a community discussion list.
  • If you like to join DBpedia developers discussion and technical discussions sign up in Slack
  • Developer Discussion
  • Become a DBpedia Student and sign up for free at the DBpedia Association. We offer special programs that provide training and other opportunities to learn about DBpedia and extend your Semantic Web and programming skills

We are looking forward to working with you!

You don’t have enough of DBpedia yet? Stay tuned and join us on facebook, twitter or subscribe to our newsletter for the latest news!

 

Have a great weekend!

Your

DBpedia Association


This material is Open Knowledge


       


For a recent overview paper about DBpedia, please refer to: