Tag Archives: datasets

The Release Circle – A Glimpse behind the Scenes

As you already know, with the new DBpedia strategy the mode of releases changed, too.  The DBpedia release process follows a three-step approach – Extraction – ID-Management and Fusion. Releases are currently published on a monthly basis. In this post, we give you insight into what the single steps of the release process comprise and what our developers actually do when preparing a DBpedia release.

Extraction  – Step one of the Release

The good news is: Our new release mode is taking shape and noticeable picked up speed. Finally the 2018-08 and, additionally the 2018.09.12 and the 2018.10.16 Releases are now available in our LTS repository.

The 2018-08 Release was generated on the basis of the Wikipedia datasets extracted in early August and currently comprises 136 languages. The extraction release contains the raw extracted data generated by the DBpedia extraction-framework. The post-processing steps, such as data-deduplication or URI-normalization are omitted and moved to later parts of the release process. Thus, we can provide direct, transparent access to the generated data in every step. Until we manage two releases per month, our data is mostly based on the second Wikipedia datasets of the previous month. In line with that, the 2018.09.12 release is based on late August data and the recent 2018.10.16 Release is based on Wikipedia datasets extracted on September 20th. They all comprise 136 languages and contain a stable list of datasets since the 2018-08 release.

Our releases are now ready for parsing and external use. Additionally, there will be a new Wikidata-based release this week.

ID-Management – Step two of the Release

For a complete “new DBpedia” release the DBpedia ID-Management and Fusion of the data have to be added to the process. The Databus ID Management is a process to unify various different IRIs identifying the same entities coined from different data providers. Taking datasets with overlapping domains of interest from multiple data providers, the set of IRIs denoting the entities in the source datasets are determined heuristically (e.g. excluding RDF/OWL types/classes).

Afterwards, these selected IRIs a numeric primary key, the ‘Singleton ID’. The core of the ID Management process happens in the next step: Based on the large set of owl:sameAs assertions in the input data with high confidence, the connected components induced from the corresponding sameAs-graph is computed. In other words: The groups of all entities from the input datasets (transitively) reachable from one to another are determined. We dubbed these groups the sameAs-clusters. For each sameAs-cluster we pick one member as representant, which determines the ‘Cluster ID’ or ‘Global Identifier’ for all cluster members.

Apart from being an essential preparatory step for the Fusion, these Global Identifiers serve purpose in their own right as unified Linked Data identifiers for groups of Linked Data entities that should be viewed as equivalent or ‘the same thing’.

A processing workflow based on Apache Spark to perform the process described on above for large quantities of RDF input data is already in place and has been run successfully for a large set of DBpedia inputs consisting of:

 

Fusion – Step three of the Release

Based on the extraction and the ID-Management, the Data Fusion finalizes the last step of the  DBpedia release cycle. With the goal of improving data quality and data coverage, the process uses the DBpedia global IRI clusters to fuse and enrich the source datasets. The fused data contains all resource of the input datasets. The fusion process is based on a functional property decision to decide the number of selected values ( owl:FunctionalProperty determination ). Further, the value selection for this functional properties is based on a preference dependent on the originated source dataset. For example, preferred values for En-DBpedia over DE-DBpedia.

The enrichment improves entity-properties and -values coverage for resources only contained in the source data. Furthermore, we create provenance data to keep track of the origin of each triple. This provenance data is also used for the http-based http://global.dbpedia.org resource view.

At the moment the fused and enriched data is available for the generic, and mapping-based extractions. More datasets are still in progress.  The DBpedia-fusion data is uploading to http://downloads.dbpedia.org/repo/dev/fusion/

 

Please note we are still in the midst of the beta testing for our data release tool, so in case you do come across any errors, reporting them to us is much appreciated to fuel the testing process.

Further information regarding the releases progress can be found here: http://dev.dbpedia.org/

Next steps

We will add more releases to the repository on a monthly basis aiming for a bi-weekly release mode as soon as possible. In between the intervals, any mistakes or errors you find and report in this data can be fixed for the upcoming release. 

Currently, the generated metadata in the DataID-file is not stable. This will fluctuate and still needs to be improved and will change in the near future. 

This blog post was written with the help our DBpedia developers Robert Bielinski, Markus Ackermann and Marvin Hofer who were responsible for the work done with respect to the DBpedia releases. We like to thank them for their great work. 

Yours DBpedia Association

Beta-Test Updates

While everyone at the DBpedia Association was preparing for the SEMANTiCS Conference in Vienna, we also managed to reach an important milestone regarding the beta-test for our data release tool.

First and foremost, already 3500 files have been published with the plugin. These files will be part of the new DBpedia release and are available on our LTS repository.

Secondly, the documentation of the testing has been brought into good shape. Feel free to drop by and check it out.
Thirdly, we reached our first interoperability goal. The current metadata is sufficient to produce RSS 1.0 feeds. See here for further information. We also defined a loose roadmap on top of the readme, where interoperability to DCAT and DCAT-AP has high priority.

 

Now we have some time to support you and work one on one and also prepare the configurations to help you set up the data releases. Lastly, we already received data from DNB and SUMO, so we will start to look into these more closely.

Thanks to all the beta-testers for your nice work.

We keep you posted.

Yours

DBpedia Association

Keep using DBpedia!

Just recently, DBpedia Association member and hosting specialist, OpenLink released the DBpedia Usage report, a periodic report on the DBpedia SPARQL endpoint and associated Linked Data deployment.

The report not only gives some historical insight into DBpedia’s usage, number of visits and hits per day but especially shows statistics collected between October 2016 and December 2017. The report covers more than a year of logs from the DBpedia web service operated by OpenLink Software at http://dbpedia.org/sparql/.  

Before we want to highlight a few aspects of DBpedia’s usage we would like to thank Open Link for the continuous hosting of the DBpedia Endpoint and the creation of this report

The graph shows the average number of hits/requests per day that were made to the DBpedia service during each of the releases.
The graph shows the average number of unique visits per day made to the DBpedia service during each of the datasets.

Speaking of which, as you can see in the following tables, there has been a massive increase in the number of hits coinciding with the DBpedia 2015–10 release on April 1st, 2016.

 

 

 

 

This boost can be attributed to an intensive promotion of DBpedia via community meetings, communication with various partners in the Linked Data community and Social media presence among the community, in order to increase backlinks.

Since then, not only the numbers of hits increased but DBpedia also provided for better data quality. We are constantly working on improving accessibility, data quality and stability of the SPARQL endpoint. Kudos to Open Link for maintaining the technical baseline for DBpedia.

The table shows the usage overview of last year.

The full report is available here.

 

Subscribe to the DBpedia Newsletter, check our DBpedia Website and follow us on Twitter, Facebook, and LinkedIn for the latest news.

Thanks for reading and keep using DBpedia!

Yours DBpedia Associaton

 

New DBpedia Release – 2016-10

We are happy to announce the new DBpedia Release.

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.

 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).

Read more

 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!