With part  II of our growth hack series, we would like to introduce you to the latest feature of our development – the new DBpedia Forum.

Why a new forum?

DBpedia has an inclusionist model and DBpedia is huge. At the core, there is data extracted from Wikipedia and Wikidata. Around this, there are derived datasets like the fusion/enrichment and also LHD. Additionally, we offer services such as DBpedia Spotlight, DBpedia Lookup, SameAs, and not to forget the main endpoint http://dbpedia.org/sparql as well as our DBpedia Chapters. All of this is surrounded by 25k academic papers and a vivid business network.

Since we have this inclusionist model, we believe that access to data and knowledge should be global and unified (and free where possible). That is exactly why we established the DBpedia Forum –  to further this mission. 

Welcome!

The DBpedia Forum is a shared community resource — a place to share skills, knowledge, and interests through an ongoing conversation about DBpedia and related topics. It is meant (among others) to replace our old support page for assistance with DBpedia. In the long run, we will shut down our (former) support page, as it is not serving our growing needs anymore. 

Where are all the DBpedians?

We figured, most of you are already actively involved in exchange about DBpedia. However, the majority of that is scattered all over the web which makes it hard for us and others to keep track of. With the new forum, we offer you a playground for vivid exchange, and to meet and greet fellow DBpedians – a platform for everyone’s benefit. 

The DBpedia Forum simplifies communication

Make this a great place for discussion by contributing yourself. It is super easy. Just visit https://forum.dbpedia.org/, browse the topics, and find the info that helps you or add your own. If you want to contribute just register and off you go. Improve the discussion by discovering ones that are already happening. Help us influence the future of the DBpedia community by engaging in discussions that make this forum an interesting place to be. 

Transparency is all

To assist with maintaining an appropriate code of conduct the forum utilizes little discourse tools that enable the community to collectively identify the best (and worst) contributions. The forum tracks bookmarks, likes, flags, replies, edits, and many more. That is similar to the ranking in the old support system but much more transparent and much more fun.

For the hunter-gatherers among you, you can also earn batches for various activities  – as long as you are active.  And if you feel very passionate about a certain topic, we would gladly make you a moderator – just let us know.  

Now is the time

Since you are already talking about DBpedia somewhere on the WWW, why not do it here and now for everyone else to follow? Your knowledge and skills are key, not only for individuals in this forum but also for the whole DBpedia community. 

Happy posting and stay tuned for part III in the growth hack series. The next post will feature timbr – DBpedia SQL Semantic Knowledge Platform.

Yours,

DBpedia Association

The post DBpedia Forum – New Ways to Exchange about DBpedia appeared first on DBpedia Association.

1. What should be the priorities of the DBpedia Association in the next year?

To overview the various priorities which were mentioned, the following digest illustrates the answers in four different groups. The most frequent answer was: to increase the data quality, followed by the enlargement of the DBpedia Community through broader dissemination.

2. What should be the priorities of the DBpedia Association in the next three years?

In contrast to question one, this one is based on the priorities the DBpedia Association focuses on during the next three years. As well as in the previous overview, the specified priorities are divided into four categories.

3. What is your main interest in DBpedia?

The chart above depicts the several main interests in DBpedia. The majority of participants have an “academic & professional” (45.7%) interest in DBpedia, followed by “professional” (28.6%) and “academic” (20.0%) interests. Only 2.9% of the answers are student-related interests.

4. How should the funds of the association be used?

With respects to “How should the funds of the association be used?”, most attendees chose “service provisioning”. The “development of new DBpedia features” was the second most popular choice. Nevertheless, also “Community building” and “release production” scored many votes.

5. How should the DBpedia Association collaborate with national/language chapters?

• Agreeing on strategic goals; making sure that national contributions can be spread to other chapters, thus increasing the overall usability of DBpedia; keeping track of good practices
• Facilitating grassroots initiatives – so mainly promote and stimulate national/language initiatives
• Local events related to DBpedia tasks
• Regular events to share ideas and data
• Join other languages members onto DBpedia
• As an umbrella organization: support, mediation, and representation
• Regular exchange and involvement
• Consult, try to figure out common priorities

6. Should DBpedia open itself to contain and curate more data not directly extracted from Wikipedia?As the chart above clearly depicts, more than half of the participants are in favor of DBpedia comprising datasets not directly derived or extracted from Wikipedia. In contrast, 34.3% have the oppositional opinion and appreciate  DBpedia focussing solely on data extraction from Wikipedia.

• If yes, which other datasets should DBpedia prioritize for fusion to improve its coverage and quality?

7. Which of the following features do you consider most important?

The following diagram gives a review of particular features and their importance from the participants point of view. As the result of question one reveals, data quality is considered the most important issue by the survey participants (23.7%). The second most important features, with 17.2% each, are: the provision of datasets extracted from the Wikipedia article text, substantial collaboration/integration with WikiData and a provision of better search, respectively an exploration of user interfaces.

8. Any other question, feedback, opinion, ideas or suggestion you would like to send to the association.

• KUTGW
• Increased support of non-RDF publication formats is probably wise as an insurance policy that DBpedia will stay relevant.
• In users mailing-list being more open-minded in an easy manner and always signalling provocative postings are welcome. And I fear it is a bit late for this survey, but better late than never, my greetings to all making some thoughts about this stuff.
• DBpedia Spotlight should return Wikidata URIs by default, for stability
• Use a richer ontology without contradictions, e.g. Book-Physical vs. Book-Conceptual Work

Thank you for your input and your participation! Your priorities and opinions are of vital importance for the success of DBpedia in the future. We will discuss the implementation of your answers during our next DBpedia Board Meetings in order to find a reasonable strategic direction of the DBpedia Association for the next years.

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

Your

DBpedia Association

The post Results of the DBpedia Strategy Survey 2017 appeared first on DBpedia Association.

This release is based on updated Wikipedia dumps dating from October 2016.

You can download the new DBpedia datasets in N3 / TURTLE serialisation from http://wiki.dbpedia.org/downloads-2016-10 or directly here http://downloads.dbpedia.org/2016-10/.

This release took us longer than expected. We had to deal with multiple issues and included new data. Most notable is the addition of the NIF annotation datasets for each language, recording the whole wiki text, its basic structure (sections, titles, paragraphs, etc.) and the included text links. We hope that researchers and developers, working on NLP-related tasks, will find this addition most rewarding. The DBpedia Open Text Extraction Challenge (next deadline Mon 17 July for SEMANTiCS 2017) was introduced to instigate new fact extraction based on these datasets.

We want to thank anyone who has contributed to this release, by adding mappings, new datasets, extractors or issue reports, helping us to increase coverage and correctness of the released data.  The European Commission and the ALIGNED H2020 project for funding and general support.

You want to read more about the  New Release? Click below for further  details.[expander_maker id=”1″ more=”Read more” less=”Read less”]

 Statistics

Altogether the DBpedia 2016-10 release consists of 13 billion (2016-04: 11.5 billion) pieces of information (RDF triples) out of which 1.7 billion (2016-04: 1.6 billion) were extracted from the English edition of Wikipedia, 6.6 billion (2016-04: 6 billion) were extracted from other language editions and 4.8 billion (2016-04: 4 billion) from Wikipedia Commons and Wikidata.

In addition, adding the large NIF datasets for each language edition (see details below) increased the number of triples further by over 9 billion, bringing the overall count up to 23 billion triples.

Changes

• The NLP Interchange Format (NIF) aims to achieve interoperability between Natural Language Processing (NLP) tools, language resources and annotations. To extend the versatility of DBpedia, furthering many NLP-related tasks, we decided to extract the complete human- readable text of any Wikipedia page (‘nif_context’), annotated with NIF tags. For this first iteration, we restricted the extent of the annotations to the structural text elements directly inferable by the HTML (‘nif_page_structure’). In addition, all contained text links are recorded in a dedicated dataset (‘nif_text_links’).
  The DBpedia Association started the Open Extraction Challenge on the basis of these datasets. We aim to spur knowledge extraction from Wikipedia article texts in order to dramatically broaden and deepen the amount of structured DBpedia/Wikipedia data and provide a platform for benchmarking various extraction tools with this effort.
  If you want to participate with your own NLP extraction engine, the next deadline for the SEMANTICS 2017 is July 17th.
  We included an example of these structures in section five of the download-page of this release.
• A considerable amount of work has been done to streamline the extraction process of DBpedia, converting many of the extraction tasks into an ETL setting (using SPARK). We are working in concert with the Semantic Web Company to further enhance these results by introducing a workflow management environment to increase the frequency of our releases.

In case you missed it, what we changed in the previous release (2016-04)

• We added a new extractor for citation data that provides two files:
  • citation links: linking resources to citations
  • citation data: trying to get additional data from citations. This is a quite interesting dataset but we need help to clean it up
• In addition to normalised datasets to English DBpedia (en-uris), we additionally provide normalised datasets based on the DBpedia Wikidata (DBw) datasets (wkd-uris). These sorted datasets will be the foundation for the upcoming fusion process with wikidata. The DBw-based uris will be the only ones provided from the following releases on.
• We now filter out triples from the Raw Infobox Extractor that are already mapped. E.g. no more “<x> dbo:birthPlace <z>” and “<x> dbp:birthPlace|dbp:placeOfBirth|… <z>” in the same resource. These triples are now moved to the “infobox-properties-mapped” datasets and not loaded on the main endpoint. See issue 22 for more details.
• Major improvements in our citation extraction. See here for more details.
• We incorporated the statistical distribution approach of Heiko Paulheim in creating type statements automatically and providing them as additional datasets (instance_types_sdtyped_dbo).

Upcoming Changes

• DBpedia Fusion: We finally started working again on fusing DBpedia language editions. Johannes Frey is taking the lead in this project. The next release will feature intermediate results.
• Id Management: Closely pertaining to the DBpedia Fusion project is our effort to introduce our own Id/IRI management, to become independent of Wikimedia created IRIs. This will not entail changing out domain or entity naming regime, but providing the possibility of adding entities of any source or scope.
• RML Integration: Wouter Maroy did already provide the necessary groundwork for switching the mappings wiki to an RML based approach on Github. Wouter started working exclusively on implementing the Git based wiki and the conversion of existing mappings last week. We are looking forward to the consequent results of this process.
• Further development of SPARK Integration and workflow-based DBpedia extraction, to increase the release frequency.

New Datasets

• New languages extracted from Wikipedia:

South Azerbaijani (azb), Upper Sorbian (hsb), Limburgan (li), Minangkabau (min), Western Mari (mrj), Oriya (or), Ossetian (os)

• SDTypes: We extended the coverage of the automatically created type statements (instance_types_sdtyped_dbo) to English, German and Dutch.
• Extensions: In the extension folder (2016-10/ext) we provide two new datasets (both are to be considered in an experimental state:
  • DBpedia World Facts: This dataset is authored by the DBpedia Association itself. It lists all countries, all currencies in use and (most) languages spoken in the world as well as how these concepts relate to each other (spoken in, primary language etc.) and useful properties like iso codes (ontology diagram). This Dataset extends the very useful LEXVO dataset with facts from DBpedia and the CIA Factbook. Please report any error or suggestions in regard to this dataset to Markus.
  • JRC-Alternative-Names: This resource is a link based complementary repository of spelling variants for person and organisation names. The data is multilingual and contains up to hundreds of variations entity. It was extracted from the analysis of news reports by the Europe Media Monitor (EMM) as available on JRC-Names.

 Community

The DBpedia community added new classes and properties to the DBpedia ontology via the mappings wiki. The DBpedia 2016-04 ontology encompasses:

• 760 classes
• 1,105 object properties
• 1,622 datatype properties
• 132 specialised datatype properties
• 414 owl:equivalentClass and 220 owl:equivalentProperty mappings external vocabularies

The editor community of the mappings wiki also defined many new mappings from Wikipedia templates to DBpedia classes. For the DBpedia 2016-10 extraction, we used a total of 5887 template mappings (DBpedia 2015-10: 5800 mappings). The top language, gauged by the number of mappings, is Dutch (648 mappings), followed by the English community (606 mappings).[/expander_maker]

 Credits to

• Markus Freudenberg (University of Leipzig / DBpedia Association) for taking over the whole release process and creating the revamped download & statistics pages.
• Dimitris Kontokostas (University of Leipzig / DBpedia Association) for conveying his considerable knowledge of the extraction and release process.
• All editors that contributed to the DBpedia ontology mappings via the Mappings Wiki.
• The whole DBpedia Internationalization Committee for pushing the DBpedia internationalization forward.
• Václav Zeman and the whole LHD team (University of Prague) for their contribution of additional DBpedia types
• Alan Meehan (TCD) for performing a big external link cleanup
• Aldo Gangemi (LIPN University, France & ISTC-CNR, Italy) for providing the links from DOLCE to DBpedia ontology.
• SpringerNature for offering a co-internship to a bright student and developing a closer relation to DBpedia on multiple issues, as well as Links to their SciGraph subjects.
• Kingsley Idehen, Patrick van Kleef, and Mitko Iliev (all OpenLink Software) for loading the new data set into the Virtuoso instance that provides 5-Star Linked Open Data publication and SPARQL Query Services.
• OpenLink Software (http://www.openlinksw.com/) collectively for providing the SPARQL Query Services and Linked Open Data publishing infrastructure for DBpedia in addition to their continuous infrastructure support.
• Ruben Verborgh from Ghent University – imec for publishing the dataset as Triple Pattern Fragments, and imec for sponsoring DBpedia’s Triple Pattern Fragments server.
• Ali Ismayilov (University of Bonn) for extending and cleaning of the DBpedia Wikidata dataset.
• All the GSoC students and mentors which have directly or indirectly worked on the DBpedia release
• Special thanks to members of the DBpedia Association, the AKSW and the Department for Business Information Systems of the University of Leipzig.

The work on the DBpedia 2016-10 release was financially supported by the European Commission through the project ALIGNED – quality-centric, software and data engineering.

More information about DBpedia is found at http://dbpedia.org as well as in the new overview article about the project available at http://wiki.dbpedia.org/Publications.

Have fun with the new DBpedia 2016-10 release!

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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:

• Ismael Rodriguez – DBpedia Mapping Front-End Administration 
• Ram Ganesan Athreya – First Chatbot for DBpedia
• Nausheen Fatma – Knowledge base embeddings for DBpedia
• Akshay Jagatap – Knowledge Base Embeddings for DBpedia
• Luca Virgili – The table extractor 
• Shashank Motepalli – Unsupervised Learning of DBpedia Taxonomy
• Krishanu Konar – Wikipedia List-Extractor

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

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Four times per year we will inform the DBpedia community about meetings, new collaborations and other topics related to DBpedia. So make sure to subscribe to our NEWSLETTER and do not miss any news.

Your DBpedia Association

The post STAY TUNED AND SIGN UP FOR THE DBPEDIA NEWSLETTER appeared first on DBpedia Association.

What is GSoC?

Google Summer of Code is a global program focused on bringing more student developers into open source software development. Funds will given to students (BSc, MSc, PhD) to work for three months on a specific task. At first open source organizations announce their student projects and then students should contact the mentor organizations they want to work with and write up a project proposal for the summer. After a selection phase, students are matched with a specific project and a set of mentors to work on the project during the summer.

If you are a GSoC student who wants to apply to our organization, please check our guideline here: http://wiki.dbpedia.org/gsoc2017

Here you can see the Google Summer of Code 2017 timeline:

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

We are looking forward to your input.

Your DBpedia Association

The post DBpedia @ GSoC 2017 – Call for students appeared first on DBpedia Association.

Sören Auer and the DBpedia Board members prepared a survey to assess the direction of the DBpedia Association. We would like to know what you think should be our priorities and how you would like the funds of the association to be used.

Your opinion counts – so please contribute actively in developing a better DBpedia. If you use DBpedia and want us to keep going forward, we kindly invite you to vote here: https://goo.gl/forms/rDqLcwL823Ok09Uw2

We will publish the results in anonymized, aggregated form on the DBpedia website.

We are looking forward to your input. Check our website for further updates, follow us on #twitter or subscribe to our newsletter.

Your DBpedia Association

The post DBpedia strategy survey appeared first on DBpedia Association.

As previous years, we would like your input for DBpedia related project ideas for GSoC 2017.

For those who are unfamiliar with GSoC (Google Summer of Code), Google pays students (BSc, MSc, PhD) to work for 3 months on an open source project. Open source organizations announce their student projects and students apply for projects they like. After a selection phase, students are matched with a specific project and a set of mentors to work on the project during the summer.

Here you can see the Google Summer of Code 2017 timeline: https://developers.google.com/open-source/gsoc/timeline

or please check:  http://wiki.dbpedia.org/gsoc2016

If you have a cool idea for DBpedia or want to co-mentor an existing cool idea go here (All mentors get a free Google T-shirt and get the chance to go Google HQs in November.).

DBpedia applied for the fifth time to participate in the Google Summer of Code program. Here you will find a list of all projects and students from GSoC 2016: http://blog.dbpedia.org/2016/04/26/dbpedia-google-summer-of-code-2016/

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

Looking forward to your input.

Your DBpedia Association

The post DBpedia @ GSoC 2017 – Call for ideas & mentors appeared first on DBpedia Association.

Hereby we proudly announce that DBpedia in Dutch is the first chapter which signed the Memorandum of Understanding (MoU). There are various intentions why they already signed the MoU: First of all they support the goals of the DBpedia Association, secondly they strengthen their own chapter and community of contributors and thirdly they improve the cooperation with the Dutch research infrastructure and the Dutch Digital Heritage. The cooperation was initiated by Koninklijke Bibliotheek (National Library of the Netherlands) and Huygens ING (research institute of History and Culture).

Other partners like imec/Ghent University and Institute of Sound and Vision have signed as well and became an executive partner of the DBpedia Association. The Vrije Universiteit will join soon. It is a cooperation between these Dutch organizations as well as the NL-DBpedia community.

The Dutch Chapter has provided a Sample DBpedia Chapter Memorandum of Understanding (MoU) to use as a template for further chapters. If you use DBpedia and want us to keep going forward, we kindly invite you to donate and help DBpedia to grow. If you would like to become a member of the DBpedia Association, please go directly to the application form or contact us.

Check our website for further updates, stay tuned and follow us on Twitter.

Your DBpedia Association

The post DBpedia in Dutch: formalizing the chapter by signing the Memorandum of Understanding appeared first on DBpedia Association.

You can download the new DBpedia datasets in a variety of RDF-document formats from: http://wiki.dbpedia.org/downloads-2016-04 or directly here: http://downloads.dbpedia.org/2016-04/

Support DBpedia

During the latest DBpedia meeting in Leipzig we discussed about ways to support DBpedia and what benefits this support would bring. For the next two months, we are aiming to raise money to support the hosting of the main services and the next DBpedia release (especially to shorten release intervals). On top of that we need to buy a new server to host DBpedia Spotlight that was so generously hosted so far by third parties. If you use DBpedia and want us to keep going forward, we kindly invite you to donate here or become a member of the DBpedia association.

Statistics

The English version of the DBpedia knowledge base currently describes 6.0M entities of which 4.6M have abstracts, 1.53M have geo coordinates and 1.6M depictions. In total, 5.2M resources are classified in a consistent ontology, consisting of 1.5M persons, 810K places (including 505K populated places), 490K works (including 135K music albums, 106K films and 20K video games), 275K organizations (including 67K companies and 53K educational institutions), 301K species and 5K diseases. The total number of resources in English DBpedia is 16.9M that, besides the 6.0M resources, includes 1.7M skos concepts (categories), 7.3M redirect pages, 260K disambiguation pages and 1.7M intermediate nodes.

Altogether the DBpedia 2016-04 release consists of 9.5 billion (2015-10: 8.8 billion) pieces of information (RDF triples) out of which 1.3 billion (2015-10: 1.1 billion) were extracted from the English edition of Wikipedia, 5.0 billion (2015-04: 4.4 billion) were extracted from other language editions and 3.2 billion (2015-10: 3.2 billion) from  DBpedia Commons and Wikidata. In general, we observed a growth in mapping-based statements of about 2%.

Thorough statistics can be found on the DBpedia website and general information on the DBpedia datasets here.

Community

The DBpedia community added new classes and properties to the DBpedia ontology via the mappings wiki. The DBpedia 2016-04 ontology encompasses:

• 754 classes (DBpedia 2015-10: 739)
• 1,103 object properties (DBpedia 2015-10: 1,099)
• 1,608 datatype properties (DBpedia 2015-10: 1,596)
• 132 specialized datatype properties (DBpedia 2015-10: 132)
• 410 owl:equivalentClass and 221 owl:equivalentProperty mappings external vocabularies (DBpedia 2015-04: 407 – 221)

The editor community of the mappings wiki also defined many new mappings from Wikipedia templates to DBpedia classes. For the DBpedia 2016-04 extraction, we used a total of 5800 template mappings (DBpedia 2015-10: 5553 mappings). For the second time the top language, gauged by the number of mappings, is Dutch (646 mappings), followed by the English community (604 mappings).

(Breaking) Changes

• In addition to normalized datasets to English DBpedia (en-uris) we additionally provide normalized datasets based on the DBpedia Wikidata (DBw) datasets (wkd-uris). These sorted datasets will be the foundation for the upcoming fusion process with wikidata. The DBw-based uris will be the only ones provided from the following releases on.
• We now filter out triples from the Raw Infobox Extractor that are already mapped. E.g. no more “<x> dbo:birthPlace <z>” and “<x> dbp:birthPlace|dbp:placeOfBirth|… <z>” in the same resource. These triples are now moved to the “infobox-properties-mapped” datasets and not loaded on the main endpoint. See issue 22 for more details.
• Major improvements in our citation extraction. See here for more details.
• We incorporated the statistical distribution approach of Heiko Paulheim in creating type statements automatically and providing them as an additional datasets (instance_types_sdtyped_dbo).

In case you missed it, what we changed in the previous release (2015-10):

• English DBpedia switched to IRIs. This can be a breaking change to some applications that need to change their stored DBpedia resource URIs / links. We provide the “uri-same-as-iri” dataset for English to ease the transition.
• The instance-types dataset is now split into two files: instance-types (containing only direct types) and instance-types-transitive containing the transitive types of a resource based on the DBpedia ontology
• The mappingbased-properties file is now split into three (3) files:
  • “geo-coordinates-mappingbased” that contains the coordinated originating from the mappings wiki. the “geo-coordinates” continues to provide the coordinates originating from the GeoExtractor
  • “mappingbased-literals” that contains mapping based fact with literal values
  • “mappingbased-objects” that contains mapping based fact with object values
  • the “mappingbased-objects-disjoint-[domain|range]” are facts that are filtered out from the “mappingbased-objects” datasets as errors but are still provided
• We added a new extractor for citation data that provides two files:
  • citation links: linking resources to citations
  • citation data: trying to get additional data from citations. This is a quite interesting dataset but we need help to clean it up
• All datasets are available in .ttl and .tql serialization (nt, nq dataset were neglected for reasons of redundancy and server capacity).

Upcoming Changes

• Dataset normalization: We are going to normalize datasets based on wikidata uris and no longer on the English language edition, as a prerequisite to finally start the fusion process with wikidata.
• RML Integration: Wouter Maroy did already provide the necessary groundwork for switching the mappings wiki to a RML based approach on Github. We are not there yet but this is at the top of our list of changes.
• Starting with the next release we are adding datasets with NIF annotations of the abstracts (as we already provided those for the 2015-04 release). We will eventually extend the NIF annotation dataset to cover the whole Wikipedia article of a resource.

New Datasets

• SDTypes: We extended the coverage of the automatically created type statements (instance_types_sdtyped_dbo) to English, German and Dutch (see above).
• Extensions: In the extension folder (2016-04/ext) we provide two new datasets, both are to be considered in an experimental state:
  • DBpedia World Facts: This dataset is authored by the DBpedia association itself. It lists all countries, all currencies in use and (most) languages spoken in the world as well as how these concepts relate to each other (spoken in, primary language etc.) and useful properties like iso codes (ontology diagram). This Dataset extends the very useful LEXVO dataset with facts from DBpedia and the CIA Factbook. Please report any error or suggestions in regard to this dataset to Markus.
  • Lector Facts: This experimental dataset was provided by Matteo Cannaviccio and demonstrates his approach to generating facts by using common sequences of words (i.e. phrases) that are frequently used to describe instances of binary relations in a text. We are looking into using this approach as a regular extraction step. It would be helpful to get some feedback from you.

Credits

Lots of thanks to

• Markus Freudenberg (University of Leipzig / DBpedia Association) for taking over the whole release process and creating the revamped download & statistics pages.
• Dimitris Kontokostas (University of Leipzig / DBpedia Association) for conveying his considerable knowledge of the extraction and release process.
• All editors that contributed to the DBpedia ontology mappings via the Mappings Wiki.
• The whole DBpedia Internationalization Committee for pushing the DBpedia internationalization forward.
• Heiko Paulheim (University of Mannheim) for providing the necessary code for his algorithm to generate additional type statements for formerly untyped resources and identify and removed wrong statements. Which is now part of the DIEF.
• Václav Zeman, Thomas Klieger and the whole LHD team (University of Prague) for their contribution of additional DBpedia types
• Marco Fossati (FBK) for contributing the DBTax types
• Alan Meehan (TCD) for performing a big external link cleanup
• Aldo Gangemi (LIPN University, France & ISTC-CNR, Italy) for providing the links from DOLCE to DBpedia ontology.
• Kingsley Idehen, Patrick van Kleef, and Mitko Iliev (all OpenLink Software) for loading the new data set into the Virtuoso instance that provides 5-Star Linked Open Data publication and SPARQL Query Services.
• OpenLink Software (http://www.openlinksw.com/) collectively for providing the SPARQL Query Services and Linked Open Data publishing  infrastructure for DBpedia in addition to their continuous infrastructure support.
• Ruben Verborgh from Ghent University – iMinds for publishing the dataset as Triple Pattern Fragments, and iMinds for sponsoring DBpedia’s Triple Pattern Fragments server.
• Ali Ismayilov (University of Bonn) for extending the DBpedia Wikidata dataset.
• Vladimir Alexiev (Ontotext) for leading a successful mapping and ontology clean up effort.
• All the GSoC students and mentors which directly or indirectly influenced the DBpedia release
• Special thanks to members of the DBpedia Association, the AKSW and the department for Business Information Systems of the University of Leipzig.

The work on the DBpedia 2016-04 release was financially supported by the European Commission through the project ALIGNED – quality-centric, software and data engineering  (http://aligned-project.eu/). More information about DBpedia is found at http://dbpedia.org as well as in the new overview article about the project available at http://wiki.dbpedia.org/Publications.

Have fun with the new DBpedia 2016-04 release!

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