Following, we will give you a brief retrospective about the presentations.

Opening Session

Katja Hose – “Querying the web of data”

….on the search for the killer App.

The concept of Linked Open Data and the promise of the Web of Data have been around for over a decade now. Yet, the great potential of free access to a broad range of data that these technologies offer has not yet been fully exploited. This talk will, therefore review the current state of the art, highlight the main challenges from a query processing perspective, and sketch potential ways on how to solve them. Slides are available here.

Dan Weitzner – “timbr-DBpedia – Exploration and Query of DBpedia in SQL”

The timbr SQL Semantic Knowledge Platform enables the creation of virtual knowledge graphs in SQL. The DBpedia version of timbr supports query of DBpedia in SQL and seamless integration of DBpedia data into data warehouses and data lakes. We already published a detailed blogpost about timbr where you can find all relevant information about this amazing new DBpedia Service.

Showcase Session

Maribel Acosta – “A closer look at the changing dynamics of DBpedia mappings”

Her presentation looked at the mappings wiki and how different language chapters use and edit it. Slides are available here.

Mariano Rico – “Polishing a diamond: techniques and results to enhance the quality of DBpedia data”

DBpedia is more than a source for creating papers. It is also being used by companies as a remarkable data source. This talk is focused on how we can detect errors and how to improve the data, from the perspective of academic researchers and but also on private companies. We show the case for the Spanish DBpedia (the second DBpedia in size after the English chapter) through a set of techniques, paying attention to results and further work. Slides are available here.

Guillermo Vega-Gorgojo – “Clover Quiz: exploiting DBpedia to create a mobile trivia game”

Clover Quiz is a turn-based multiplayer trivia game for Android devices with more than 200K multiple choice questions (in English and Spanish) about different domains generated out of DBpedia. Questions are created off-line through a data extraction pipeline and a versatile template-based mechanism. A back-end server manages the question set and the associated images, while a mobile app has been developed and released in Google Play. The game is available free of charge and has been downloaded by +10K users, answering more than 1M questions. Therefore, Clover Quiz demonstrates the advantages of semantic technologies for collecting data and automating the generation of multiple-choice questions in a scalable way. Slides are available here.

Fabian Hoppe and Tabea Tiez – “The Return of German DBpedia”

Fabian and Tabea will present the latest news on the German DBpedia chapter as it returns to the language chapter family after an extended offline period. They will talk about the data set, discuss a few challenges along the way and give insights into future perspectives of the German chapter. Slides are available here.

Wlodzimierz Lewoniewski and Krzysztof Węcel  – “References extraction from Wikipedia infoboxes”

In Wikipedia’s infoboxes, some facts have references, which can be useful for checking the reliability of the provided data. We present challenges and methods connected with the metadata extraction of Wikipedia’s sources. We used DBpedia Extraction Framework along with own extensions in Python to provide statistics about citations in 10 language versions. Provided methods can be used to verify and synchronize facts depending on the quality assessment of sources. Slides are available here.

Wlodzimierz Lewoniewski – “References extraction from Wikipedia infoboxes” … He gave insight into the process of extracting references for Wikipedia infoboxes, which we will use in our GFS project.

Afternoon Session

Sebastian Hellmann, Johannes Frey, Marvin Hofer – “The DBpedia Databus – How to build a DBpedia for each of your Use Cases”

The DBpedia Databus is a platform that is intended for data consumers. It will enable users to build an automated DBpedia-style Knowledge Graph for any data they need. The big benefit is that users not only have access to data, but are also encouraged to apply improvements and, therefore, will enhance the data source and benefit other consumers. We want to use this session to officially introduce the Databus, which is currently in beta and demonstrate its power as a central platform that captures decentrally created client-side value by consumers.  

We will give insight on how the new monthly DBpedia releases are built and validated to copy and adapt for your use cases. Slides are available here.

Interactive session, moderator: Sebastian Hellmann – “DBpedia Connect & DBpedia Commerce – Discussing the new Strategy of DBpedia”

In order to keep growing and improving, DBpedia has been undergoing a growth hack for the last couple of months. As part of this process, we developed two new subdivisions of DBpedia: DBpedia Connect and DBpedia Commerce. The former is a low-code platform to interconnect your public or private databus data with the unified, global DBpedia graph and export the interconnected and enriched knowledge graph into your infrastructure. DBpedia Commerce is an access and payment platform to transform Linked Data into a networked data economy. It will allow DBpedia to offer any data, mod, application or service on the market. During this session, we will provide more insight into these as well as an overview of how DBpedia users can best utilize them. Slides are available here.

In case you missed the event, all slides and presentations are also available on our Website. Further insights, feedback and photos about the event are available on Twitter via #DBpediaDay

We are now looking forward to more DBpedia meetings next year. So, stay tuned and check Twitter, Facebook and the Website or subscribe to our Newsletter for the latest news and information.

If you want to organize a DBpedia Community meeting yourself, just get in touch with us via dbpedia@infai.org regarding program and organization.

Yours

DBpedia Association

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DBpedia Live is a long term core project of DBpedia that immediately extracts fresh triples from all changed Wikipedia articles. After a long hiatus, fresh and live updated data is available once again, thanks to our former co-worker Lena Schindler whose work we feature in this blog post. Before we dive into Lena’s report, let’s have a look at some general info about DBpedia Live:

• DBpedia Live Website 
• DBpedia Live Changeset Downloads 
• Shared Public DBpedia Live SPARQL Endpoint

Live Enterprise Version

OpenLink Software provides a scalable, dedicated, live Virtuoso instance, built on Lena’s remastering. Kingsley Idehen announced the dedicated business service in our new DBpedia forum. .
On the Databus, we collect publicly shared and business-ready dedicated services in the same place where you can download the data. Databus allows you to download the data, build a service, and offer that service, all in one place. Data up-loaders can also see who builds something with their data

Remastering the DBpedia Live Module

Contribution by Lena Schindler

After developing the DBpedia REST API as part of a student project in 2018, I worked as a student Research Assistant for DBpedia. My task was to analyze and patch severe issues in the DBpedia Live instance. I will shortly describe the purpose of DBpedia Live, the reasons it went out of service, what I did to fix these, and finally, the changes needed to support multi-language abstract extraction.

Overview

The DBpedia Extraction Framework is Scala-based software with numerous features that have evolved around extracting knowledge (as RDF) from Wikis. One part is the DBpedia Live module in the “live-deployed” branch, which is intended to provide a continuously updated version of DBpedia by processing Wikipedia pages on demand, immediately after they have been modified by a user. The backbone of this module is a queue that is filled with recently edited Wikipedia pages, combined with a relational database, called Live Cache, that handles the diff between two consecutive versions of a page. The module that fills the queue, called Feeder, needs some kind of connection to a Wiki instance that reports changes to a Wiki Page. The processing then takes place in four steps: 

1. A wiki page is taken out of the queue. 
2. Triples are extracted from the page, with a given set of extractors. 
3. The new triples from the page are compared to the old triples from the Live Cache.
4. The triple sets that have been deleted and added are published as text files, and the Cache is updated. 

Background

DBpedia Live has been out of service since May 2018, due to the termination of the Wikimedia RCStream Service, upon which the old DBpedia Live Feeder module relied. This socket-based service provided information about changes to an existing Wikimedia instance and was replaced by the EventStreams service, which runs over a single HTTP connection using chunked transfer encoding, and is following the Server-Sent Event (SSE) protocol. It provides a stream of events, each of which contains information about title, id, language, author, and time of every page edit of all Wikimedia instances.

Fix

Starting in September 2018, my first task was to implement a new Feeder for DBpedia Live that is based on this new Wikimedia EventStreams Service. For the Java world, the Akka framework provides an implementation of a SSE client. Akka is a toolkit developed by Lightbend. It simplifies the construction of concurrent and distributed JVM applications, enabling both Java and Scala access. The Akka SSE client and the Akka Streams module are used in the new EventStreamsFeeder (Akka Helper) to extract and process the data stream. I decided to use Scala instead of Java, because it is a more natural fit to Akka. 

After I was able to process events, I had the problem that frequent interruptions in the upstream connection were causing the processing stream to fail. Luckily, Akka provides a fallback mechanism with back-off, similar to the Binary Exponential Backoff of the Ethernet protocol which I could use to restart the stream (called “Graph” in Akka terminology).

Another problem was that in many cases, there were many changes to a page within a short time interval, and if events were processed quickly enough, each change would be processed separately, stressing the Live Instance with unnecessary load. A simple “thread sleep” reduced the number of change-sets being published every hour from thousands to a few hundred.

Multi-language abstracts

The next task was to prepare the Live module for the extraction of abstracts (typically the first paragraph of a page, or the text before the table of contents). The extractors used for this task were re-implemented in 2017. It turned out to be a configuration issue first, and second a candidate for long debugging sessions, fixing issues in the dependencies  between the “live” and “core” modules. Then, in order to allow the extraction of abstracts in multiple languages, the “live” module needed many small changes, at places spread across the code-base, and care had to be taken not to slow down the extraction in the single language case, compared to the performance before the change. Deployment was delayed by an issue with the remote management unit of the production server, but was accomplished by May 2019.

Summary

I also collected my knowledge of the Live module in detailed documentation, addressed to developers who want to contribute to the code. This includes an explanation of the architecture as well as installation instructions. After 400 hours of work, DBpedia Live is alive and kicking, and now supports multi-language abstract extraction. Being responsible for many aspects of Software Engineering, like development, documentation, and deployment, I was able to learn a lot about DBpedia and the Semantic Web, hone new skills in database development and administration, and expand my programming experience using Scala and Akka. 

“Thanks a lot to the whole DBpedia Team who always provided a warm and supportive environment!”

Thank you Lena, it is people like you who help DBpedia improve and develop further, and help to make data networks a reality.

Follow DBpedia on LinkedIn, Twitter or Facebook and stop by the DBpedia Forum to check out the latest discussions.

Yours DBpedia Association

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