TerminusDB and DBpedia

Friday, November 27, 2020 - 10:51am

DBpedia Member Features – In the coming weeks, we will give DBpedia members the chance to present special products, tools and applications and share them with the community. We will publish several posts in which DBpedia members provide unique insights. This week TerminusDB will show you how to use TerminusDB’s unique collaborative features to access DBpedia data. Have fun while reading!

by Luke Feeney from TerminusDB

This post introduces TerminusDB as a member of the DBpedia Association – proudly supporting the important work of DBpedia. It will also show you how to use TerminusDB’s unique collaborative features to access DBpedia data.

TerminusDB – an Open Source Knowledge Graph

TerminusDB is an open-source knowledge graph database that provides reliable, private & efficient revision control & collaboration. If you want to collaborate with colleagues or build data-intensive applications, nothing will make you more productive.

TerminusDB provides the full suite of revision control features and TerminusHub allows users to manage access to databases and collaboratively work on shared resources.

  • Flexible data storage, sharing, and versioning capabilities
  • Collaboration for your team or integrated in your app
  • Work locally then sync when you push your changes
  • Easy querying, cleaning, and visualization
  • Integrate powerful version control and collaboration for your enterprise and individual customers.

The TerminusDB project originated in Trinity College Dublin in Ireland in 2015. From its earliest origins, TerminusDB worked with DBpedia through the ALIGNED project, which was a research project funded by Horizon 2020 that focused on building quality-centric software for data management.

ALIGNED Project with early TerminusDB (then called ‘Dacura’) and DBpedia


While working on this project and especially our work building the architecture behind Seshat: The Global History Databank, we needed a solution that could enable collaboration among a highly distributed team on a shared database whose primary function was the curation of high-quality datasets with a very rich structure. While the scale of data was not particularly large, the complexity was extremely high. Unfortunately, the linked-data and RDF toolchains was severely lacking – we evaluated several tools in an attempt to architect a solution; however, in the end we were forced to build an end-to-end ourselves.

Evolution of TerminusDB

In general, we think that computers are fantastic things because they allow you to leverage much more evidence when making decisions than would otherwise be possible. It is possible to write computer programs that automate the ingestion and analysis of unimaginably large quantities of data.

If the data is well chosen, it is almost always the case that computational analysis reveals new and surprising insights simply because it incorporates more evidence than could possibly be captured by a human brain. And because the universe is chaotic and there are combinatorial explosions of possibilities all over the place, evidence is always better than intuition when seeking insight.

As anybody who has grappled with computers and large quantities of data will know, it’s not as simple as that. Computers should be able to do most of this for us. It makes no sense that we are still writing the same simple and tedious data validation and transformation programs over and over ad infinitum. There must be a better way.

This is the problem that we set out to solve with TerminusDB. We identified two indispensable characteristics that were lacking in data management tools:

  1. A rich and universally machine-interpretable modelling language. If we want computers to be able to transform data between different representations automatically, they need to be able to describe their data models to one another.
  2. Effective revision control. Revision control technologies have been instrumental in turning software production from a craft to an engineering discipline because they make collaboration and coordination between large groups much more fault tolerant. The need for such capabilities is obvious when dealing with data – where the existence of multiple versions of the same underlying dataset is almost ubiquitous and with only the most primitive tool support.

TerminusDB and DBpedia

Team TerminusDB took part in the DBpedia Autumn Hackathon 2020. As you know, DBpedia is an extract of the structured data from Wikipedia.

Our Hackathon Project Board

You can read all about our DBpedia Autumn Hackathon adventures in this blog post.

Open Source

Unlike many systems in the graph database world, TerminusDB is committed to open source. We believe in the principals of open source, open data and open science. We welcome all those data people that want to contribute to the general good of the world. This is very much in alignment with the DBpedia Association and community.

DBpedia on TerminusHub

TerminusHub is the collaborative point between TerminusDBs. You can push data to you colleagues and collaborators, you can pull updates (efficiently – just the diffs) and you can clone databases that are made available on the Hub (by the TerminusDB team or by others). Think of it as GitHub, but for data.

The DBpedia database is available on TerminusHub. You can clone the full DB in a couple of minutes (depending on your internet connection of course) and get querying. TerminusDB uses succinct data structures to compress everything so it makes sharing large database feasible – more technical detail here: https://github.com/terminusdb/terminusdb/blob/dev/docs/whitepaper/terminusdb.pdf for interested parties.

TerminusDB in the DBpedia Association

We will contribute to DBpedia by working to improve the quality of data available, by introducing new datasets that can be integrated with DBpedia, and by participating fully in the community.

We are looking forward to a bright future together.

A big thank you to Luke and TerminusDB presenting how TerminusDB works and how they would like to work with DBpedia in the future.

Yours,

DBpedia Association

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GNOSS – How do we envision our future work with DBpedia

Tuesday, November 17, 2020 - 9:23pm

DBpedia Member Features – In the coming weeks, we will give DBpedia members the chance to present special products, tools and applications and share them with the community. We will publish several posts in which DBpedia members provide unique insights. This week GNOSS will give an overview of their products and business focus. Have fun while reading!

 by Irene Martínez and Susana López from GNOSS

GNOSS (https://www.gnoss.com/) is a Spanish technology manufacturing company that has developed its own platform for the construction and exploitation of knowledge graphs. GNOSS technology operates within the framework of the set of technologies that concur in the Artificial Intelligence Program semantically interpreted: NLU (Natural Language Understanding); identification, extraction, disambiguation and linking of entities; as well as the construction of interrogation and knowledge discovery systems based on inferences and on systems that emulate the forms of natural reasoning.

How is our business focus

The GNOSS project is positioned in the emerging market for Deep AI (Deep Understanding AI). By Deep AI we mean the convergence of symbolic AI and sub-symbolic AI.

GNOSS is the leading company in Spain in the construction of solutions aimed at the construction of knowledge ecosystems interpretable and queryable (interrogable) by machines and people, which integrate heterogeneous and distributed data represented by technical vocabularies and ontologies written in programming languages (OWL-RDF ) interpretable by machines, which are consolidated and exploited through knowledge graphs

The technology developed by GNOSS facilitates the construction, within the framework of the aforementioned ecosystems, of intelligent interrogation and search systems, information enrichment and context generation systems, advanced recommendation systems, predictive Business Intelligence systems based on dynamic visualizations and NLP/NLU systems.

GNOSS works in the cloud and is offered as a service. We have a complex and robust technological infrastructure designed to compute intelligent data in a framework that offers the maximum guarantee of security and best practices in technology services.

Products and Solutions

PRODUCTS

GNOSS Knowledge Graph Builder is a development platform upon which third parties can deploy their web projects, with a complete suite of components to build Knowledge Graphs and deploy an intelligent web semantically aware in record time. The platform enables the interrogation of a Knowledge Graph by both machines and people. The main modules of the platform are 1) Metadata and Knowledge Graph Construction and Management; 2)Discovery, reasoning and analysis through Knowledge Graphs; 3) Semantic Content Management. It also includes some configurable characteristics and functions for fast, agile and flexible adaptation and evolution of intelligent digital ecosystems

SOLUTIONS

Thanks to GNOSS Knowledge Graph Builder and GNOSS Sherlock Services, we have developed a suite of transversal solutions and some sectorial solutions based on the creation and exploitation of Knowledge Graphs.

The transversal solutions are: GNOSS Metadata Management Solution (for the integration of heterogeneous and distributed information into semantic data layer consolidating information into a knowledge graph), GNOSS Sherlock NLP-NLU Service (Intelligent software services for machines to understand us, based on natural language processing and on entity recognition and linking; and dynamic graphic visualizations), GNOSS Search Cloud (which includes intelligent information search, interrogation and retrieval systems; inferences; recommendations and generation of significant contexts), GNOSS Semantic BI&Analytics (expressive and dynamic Business Intelligence based on Smart Data).

We have developed sectorial solutions in Education and University, Tourism, Culture and Museums, Healthcare, Communication and MK, Banking, Public Administration; Catalogs and support to supply chain.

What significance does DBpedia for us

We think that the foundations for the construction of the great European Project of Symbolic AI are being created thanks to DBpedia and other Linked Open Data projects, by turning the internet into a Universal Knowledge Base, which works according to the principles and standards of Linked Open Data and Semantic Web. This knowledge base, as the brain of the internet, would be the basis of the IA of the future. In this context, we consider that DBpedia plays a central role as an open general knowledge base and, therefore, as the core of the European Project of Symbolic AI.

Currently, some projects developed with GNOSS platform are already using DBpedia to access a large amount of structured and ontologically-represented information, in order to link entities, enrich information and offer contextual information. Two examples of this are the ‘Augmented Reading’ of Museo del Prado in the descriptions of the artworks of the Museum Prado, and the Graph of related entities in Didactalia.net.

The ‘Augmented Reading’ of Museo del Prado in the descriptions of the artworks of the Museum (see for instance ‘The Family of Carlos IV’, by Francisco de Goya) recognizes and extracts the entities contained in them, thereby providing additional and contextual information about them, so that anyone who can read them without giving up understanding them in depth.

In Didactalia.net, for a given educational resource, its Graph of related entities works as a conceptual map of the resource to support the teacher and the student in the teaching-learning process (see for instance this resource about Descartes).

How do we envision our future work with DBpedia

GNOSS can contribute to DBpedia at different levels, from making suggestions for further development to participating in strategy and commercialization.

We could collaborate with DBpedia contributing to tests of the releases of DBpedia and giving our feedback of the use of DBpedia in projects applied to public and private organizations developed with GNOSS. Based on this, we could make suggestions for future work considering our experience and customer needs in this context.

We could participate in the strategy and commercialization, in order to gain more presence in sectors in which we work, such as healthcare, education, culture or communication, and to achieve that the private companies can appreciate and benefit from the great value that DBpedia can offer them.

A big thank you to GNOSS for presenting their product and envisioning how they would like to work with DBpedia in the future.

Yours,

DBpedia Association

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Ontotext GraphDB on DBpedia

Friday, November 6, 2020 - 9:57am

DBpedia Member Features – In the coming weeks we will give DBpedia members the chance to present special products, tools and applications and share them with the community. We will publish several posts in which DBpedia members provide unique insights. Ontotext will start with the GraphDB database. Have fun while reading!

 by Milen Yankulov from Ontotext

GraphDB is a family of highly efficient, robust, and scalable RDF databases. It streamlines the load and use of linked data cloud datasets, as well as your own resources. For easy use and compatibility with the industry standards, GraphDB implements the RDF4J framework interfaces, the W3C SPARQL Protocol specification, and supports all RDF serialization formats. The database offers open source API and it is the preferred choice of both small independent developers and big enterprise organizations because of its community and commercial support, as well as excellent enterprise features such as cluster support and integration with external high-performance search applications – Lucene, Solr, and Elasticsearch. GraphDB is build 100% on Java in order to be OS Platform independent.

GraphDB is one of the few triplestores that can perform semantic inferencing at scale, allowing users to derive new semantic facts from existing facts. It handles massive loads, queries, and inferencing in real-time.

GDB Architecture

GraphDB Workbench

Workbench is the GraphDB web-based administration tool. The user interface is similar to the RDF4J Workbench Web Application, but with more functionality.

GraphDB Engine

The GraphDB Workbench REST API can be used for managing locations and repositories programmatically, as well as managing a GraphDB cluster.  It includes connecting to remote GraphDB instances (locations), activating a location, and different ways for creating a repository.

It includes also connecting workers to masters, connecting masters to each other, as well monitoring the state of a cluster.

GraphQL access via Ontotext Platform 3

GraphDB enables Knowledge Graph access and updates via GraphQL. GraphDB is extended to support the efficient processing of GraphQL queries and mutations to avoid the N+1 translation of nested objects to SPARQL queries.

Ontotext offers three editions of GraphDB: Free, Standard, and Enterprise.

Free – commercial, file-based, sameAs & query optimizations, scales to tens of billions of RDF statements on a single server with a limit of two concurrent queries.

Standard Edition (SE) – commercial, file-based, sameAs & query optimizations, scales to tens of billions of RDF statements on a single server and an unlimited number of concurrent queries.

Enterprise Edition (EE) – high-availability cluster with worker and master database implementation for resilience and high-performance parallel query answering.

Why GraphDB is preferred choice of many data architects and data ops?

3 Reasons:

1. High Availability Cluster Architecture

GraphDB offers you a high-performance cluster proven to scale in production environments. It supports 

  • (1) coordinating all read and write operations, 
  • (2) ensuring that all worker nodes are synchronized,
  • (3) propagating updates (insert and delete tasks) across all workers and checking updates for inconsistencies, 
  • (4) load balancing read requests between all available worker nodes

Improved resilience

failover, dynamic configuration

Improved query bandwidth

larger cluster means more queries per unit time

Deployable across multiple data centres

Elastic scaling in cloud environments

Integration with search engines

Cluster Management and Monitoring

It supports

(1) automatic cluster reconfiguration in the event of failure of one or more worker nodes, 

(2) a smart client supporting multiple endpoints.

2. Easy Setup

GraphDB is 100% Java based in order to be Platform Independent. It is available through Native Installation Packages or Open Maven. It supports also Puppet and could be Dockerized. GraphDB is Cloud agnostic – It could be deployd on AWS, Azure, Google Cloud, etc.

3. Support

Based on the Edition you are using you could use the Community Support (StackOverFlow monitoring)

Ontotext has its Dedicated Support Team tha could assist through Customized Runbooks, Easy Slack communication, Jira Issue-Tracking System 

A big thank you to Ontotext for providing some insights into their product and database.

Yours,

DBpedia Association

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New DBpedia Usage Report

Friday, October 30, 2020 - 12:34pm

Our partner Openlink recently published a new DBpedia usage report on the SPARQL endpoint and associated Linked Data deployment

Copyright © 2020 OpenLink Software

Introduction

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 July 2017 and September 2020, spanning more than 3 years of logs from the DBpedia web service operated by our partner OpenLink Software at http://dbpedia.org/sparql/.

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

DBpedia Usage Report: Historical Overview

The first table shows the average numbers of Visits and Hits per day during the time each DBpedia dataset was live on the http://dbpedia.org/sparql endpoint. Similarly to the hits, we also see a huge increase in visits coinciding with the DBpedia 2015–10 release on April 1st, 2016.

Historic overview
Historical overview of visits and hits per day in the cause of the last 10 years.

This boost was attributed to an intensive promotion of DBpedia via community meetings, and exchange with various partners in the Linked Data community. In addition, our Social Media activity in the community increased backlinks. Since then, not only the numbers of hits rose 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 next graph shows the percentage of the total number of hits in a given time period that can be attributed to the /sparql endpoint. If we look at the historical data from 2014–09 onward, we can see the requests to /sparql were about 60.16% of the total number of hits.

DBpedia Usage Report: Current Statistics

If we focus on the last 12 months, we can see a slightly lower average of 48.10%, as shown in the graph below. This means that around 50% of traffic uses Linked Data constructions to view the information available through DBpedia. To put this into perspective, that means that of the average of 7.2 million hits to the endpoint on a given day, 3.6 million hits are Linked Data Deployment hits.

The following table shows the information on visits, sited and hits for
each month between September 2019 and 2020.

Statistical overview of the last year.
Overview of the last 12 months.

For detailed information on the specific usage numbers, please visit the original report by Openlink published here. Also, older reporst are available through their site.

Further Links

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

Thanks for reading and keep using DBpedia!

Yours DBpedia Associaton

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More than 130 knowledge graph enthusiasts joined the KGiA event.

Friday, October 16, 2020 - 2:20pm

Opening the KG in Action event

The SEMANTiCS Onsite Conference 2020 had to be postponed till September 2021. To bridge the gap until 2021, we took this opportunity to organize the Knowledge Graphs in Action (KGiA) online track as a SEMANTiCS satellite event on October 6, 2020. This new online conference is a combination of two existing events: the DBpedia Community Meeting and the annual Spatial Linked Data conference organised by EuroSDR and the Platform Linked Data Netherlands. We combined the best of both and as a bonus we added a track about Geo-information Integration organized by EuroSDR. As special joint sessions we presented four keynote speakers. 

First and foremost, we would like to thank the SEMANTiCS, EuroSDR and Platform Linked Data Netherlands for organizing the KGiA online event and many thanks to all chairs who supported the conference.

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

Opening & Keynote #1

The Knowledge Graphs in Action conference was opened with a keynote presentation ‘Data Infrastructure for Energy System Models’ by Carsten Hoyer-Klick (German Aerospace Center). He presented LOD GEOSS, a project for the development of a distributed data infrastructure for the analysis of energy systems. The project is about the development of networked database concepts based on the ideas of linked open data and the semantic web for input and output data of energy system models in energy systems analysis. Afterwards the conference chairs offered three parallel sessions in the morning. 

Morning Sessions 

Session 1: Spatial Linked Data Country Update

In this session 7 speakers presented the uptake and latest progress of Spatial Linked Data adoption in European countries, either within national mapping agencies or beyond.

Session 2: VGI country presentations

There is an increasing use of crowdsourced geo-information (CGI) in spatial data applications by National Mapping and Cadastral Agencies (NMCAs). Applications range from using CGI for supporting the actualisation of spatial data to adding extra content, such as land use, building entrances, road barriers, sensors placed in the public space and many more. This session hosted five presentations from NMCAs showing the status of their CGI integration in mapping applications and processes.

Session 3: DBpedia Member presentations

Members of the DBpedia Association presented their latest tools, applications and technical developments in this session. Filipe Mesquita (Diffbot) opened the member session with his talk ‘Beyond Human Curation: How Diffbot Is Building A Knowledge Graph of the Web’. Also ImageSnippets, timbr.ai and GNOSS gave interesting and delightful talks about their technical developments. Vassil Momtchev from Ontotext closed the session by giving insights into the GraphDB 9.4.   

For further details of the presentations follow the links to the slides on the event page.

Afternoon Sessions 

Keynote #2

The afternoon sessions started with an interesting keynote by Peter Mooney (Maynooth University). He talked about the opportunities for a more integrated approach to Geo-information integration. 

Dutch National Graph as a Digital Twin

After the second keynote Sebastian Hellmann, the CEO of the DBpedia Association, presented the development and methodology of the National Knowledge Graph for the Netherlands. In cooperation with Dutch partners, DBpedia invested two months to develop this new knowledge graph. His insightful presentation was followed by Benedicte Bucher (University Gustave Eiffel) talking about ‘Knowledge Graph on spatial digital assets in European’. She also presented the EuroSDR LDG initiative in many details.      

Afternoon Parallel Sessions

Session 4: Transforming Linked Data into a networked data economy – DBpedia Chapter Session

In the DBpedia Chapter Session, members of different European DBpedia chapters gave an overview about the data landscape in their countries. They presented identified business opportunities and important challenges, such as automated clearance of licenses in their countries. Enno Meijers (National Library of the Netherlands) summarized the data landscape in the Netherlands. There were also presentations about the data landscape in Brazil, Spain, Austria and Poland.   

Session 5: EuroSDR VGI data wrangling

This session intends to uncover new combinations and integration of CGI data with data from NMCAs which demonstrate the added value for map creation and map usage. Data wrangling (the process of creating small reproducible data processing workflows) is deployed for this work by using and combining existing geospatial software (desktop, web and mobile). In this session the results of the data wrangling process were presented. 

Session 6: Spatial Session

In this session, two speakers presented how they built knowledge graphs, and in the second part three presenters gave insights into tooling and presented the state of the art on working with Linked Data.

For further details of the presentations follow the links to the slides on the event page.

Keynote #3 and #4

Keynote #3 ‘Spatial Knowledge in Action – Deep semantics, geospatial thinking, and new cartographies’ was given by Marinos Kavouras (National Technical University of Athens). Marinos stated that the power of maps and modern cartographic language proves to have a new role for society at large, as an indispensable communication and cognitive tool. The KG in Action conference ended with the keynote presentation ‘Know, Know Where, KnowWhereGraph’ by Krzysztof Janowicz (University of California). During his live talk from California, Krzysztof provided an overview of ideas and hopes for creating geo-specific knowledge graphs and geo-enrichment services on top of this graph to address some of the aforementioned challenges.

In case you missed the event, all slides and presentations are also available on the DBpeda website. We will upload all recordings on the DBpedia youtube channel. Further insights, feedback and photos about the event are available on Twitter (#KGiA hashtag).

We are now looking forward to 2021. We plan to have meetings at the Knowledge Graph Conference and the SEMANTiCS conference in Amsterdam. Stay safe and check Twitter, LinkedIn and our Website or subscribe to our Newsletter for the latest news and information.

Yours,

DBpedia Association

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GSoC 2020 recap

Monday, October 12, 2020 - 12:45pm

With 45 project proposals, this GSoC edition marked a new record for DBpedia.

GSoc and DBpedia Sticker

Oh, what a year! For the 9th year in a row, we were part of this incredible journey of young ambitious developers who joined us as an open source organization to work on a GSoC coding project all summer. 

Each year has brought us new project ideas, many amazing students and mostly great project results that shaped the future of DBpedia. 

Even though Covid-19 changed a lot in the world, it couldn’t shake GSoC much. The program, designed to mentor youngsters from afar is almost too perfect for the current world situation. One of the advantages of Google Summer of Code is, especially in times like these, the chance to work on projects remotely, but still obtain a first deep dive into Open Source projects like us – DBpedia. 

Meet the students and their projects

This year, we had notably more applications than in the previous ones. With 45 project proposals, this GSoC edition marked a new record for DBpedia. Throughout the summer program, our seven finalists worked intensely on their challenging DBpedia projects with great outcomes to show to the public. Projects ranged from extending our DBpedia extraction framework to a DBpedia Database project as well as to an online tool to generate RDF from DBpedia abstracts. If you want to have deeper insights into our GSoC student’s work you can find their blogs and repos in the following list. Check them out! 

Thanks to all our mentors around the world for joining us in this endeavour, for mentoring with kindness and technical expertise. A huge shout out to those who have been by our side for so many years in a row. Many thanks to Tommaso Soru, Beyza Yaman, Diego Moussalem, Edgard Marx, Mariano Rico, Thiago Castro Ferreira, Luca Virgili as well as Sebastian Hellmann, Stuart Chan, Amandeep Srivastava, Julio Hernandez and Jan Forberg. 

Mentor Summit

During the previous years you might have noticed that we always organized a little lottery to decide which mentor or organization admin can join the annual GSoC mentor summit. As this year’s event will be held online, space is not limited to 300 something mentors but is open to all organization admins and mentors alike. The GSoC Virtual Mentor Summit takes place October 15- 16, 2020 and this year we hope all our mentors will find the time to join and exchange with fellow mentors from around dozens of open source projects. 

After GSoC is before the next GSoC

We can not wait for the 2021 edition. Likewise, if you are an ambitious student who is interested in open source development and working with DBpedia you are more than welcome to either contribute your own project idea or apply for project ideas we offer starting in early 2021.

In case you like to mentor a project do not hesitate to also get in touch with us via dbpedia@infai.org

Stay tuned, frequently check Twitter, LinkedIn or the DBpedia Forum to stay in touch and don’t miss your chance of becoming a crucial force in this endeavour as well as a vital member of the DBpedia community.

See you soon,

yours

DBpedia Association

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Call for Participants: DBpedia Autumn Hackathon

Friday, September 11, 2020 - 2:19pm

Dear DBpedians, Linked Data savvies and Ontologists,

We would like to invite you to join the DBpedia Autumn Hackathon 2020 as a new format to contribute to DBpedia, gain fame, win small prizes and experience the latest technology provided by DBpedia Association members. 
The hackathon is part of the Knowledge Graphs in Action conference on October 6, 2020. 

Timeline 

  • Registration of participants – main communication channel will be the #hackathon channel in DBpedia Slack (sign up, then add yourself to the channel). If you wish to receive a reminder email on Sep 21st, 2020 you can leave your email address in this form.
  • Until September 14th – preparation phase, participating organizations prepare details and track formation. Additional tracks can be proposed, please contact dbpedia-events@infai.org.
  • Announcement of details for each track, including prizes, participating data, demos as well as tools and tasks. Please check updates on the Hackathon website. – September 21st, 2020
  • Hacking period, coordinated via DBpedia slack September 21st to October 1st, 2020
  • Submission of hacking result (3 min video and 2-3 paragraph summary with links, if not stated otherwise in the track) – October 1st, 2020 at 23:59 Hawaii Time
  • Final Event, Each track chair will present a short recap of the track and announces prizes or summarizes the result of hacking. – October 5th, 2020 at 16:00 CEST
  • Knowledge Graphs in Action Event (see program) – October 6th, 2020 at 9:50 – 15:30 CEST
  • Results and videos are documented on the DBpedia Website and the DBpedia Youtube channel.

Member Tracks 

The member tracks are hosted by DBpedia Association members, who are technology leaders in the area of Knowledge Engineering. Additional tracks can be proposed until Sep 14th, please contact dbpedia-events@infai.org.

  • timbr SQL Knowledge Graph: Learn how to model, map and query ontologies in timbr and then model an ontology of GDELT, map it to the GDELT database, and answer a number of questions that currently are quite impossible to get from the BigQuery GDELT database. Cash prizes planned. 
  • GNOSS Knowledge Graph Builder: Give meaning to your organisation’s documents and data with a Knowledge Graph. 
  • ImageSnippets: Labeling images with semantic descriptions. Use DBpedia spotlight and an entity matching lookup to select DBpedia terms to describe images. Then explore the resulting dataset through searches over inference graphs and explore the ImageSnippets dataset through our SPARQL endpoint. Prizes planned. 
  • Diffbot: Build Your Own Knowledge Graph! Use the Natural Language API to extract triples from natural language text and expand these triples with data from the Diffbot Knowledge Graph (10+ billion entities, 1+ trillion facts). Check out the demo. All participants will receive access to the Diffbot KG and tools for (non-commercial) research for one year ($10,000 value).

Dutch National Knowledge Graph Track

Following the DBpedia FlexiFusion approach, we are currently flexi-fusing a huge, dbpedia-style knowledge graph that will connect many Linked Data sources and data silos relevant to the country of the Netherlands. We hope that this will eventually crystallize a well-connected sub-community linked open data (LOD) cloud in the same manner as DBpedia crystallized the original LOD cloud with some improvements (you could call it LOD Mark II). Data and hackathon details will be announced on 21st of September.

Organising committee:

Improve DBpedia Track

A community track, where everybody can participate and contribute in improving existing DBpedia components, in particular the extraction framework, the mappings, the ontology, data quality test cases, new extractors, links and other extensions. Best individual contributions will be acknowledged on the DBpedia website by anointing the WebID/Foaf profile.

(chaired by Milan Dojchinovski and Marvin Hofer from the DBpedia Association & InfAI and the DBpedia Hacking Committee, please message @m1ci to volunteer to the hacking committee)

DBpedia Open Innovation Track 

(not part of the hackathon, pre-announcement)

For the DBpedia Spring Event 2021, we are planning an Open Innovation Track, where DBpedians can showcase their applications. This endeavour will not be part of the hackathon as we are looking for significant showcases with development effort of months & years built on the core infrastructure of DBpedia such as the SPARQL endpoint, the data, lookup, spotlight, DBpedia Live, etc. Details will be announced during the Hackathon Final Event on October 5.  

(chaired by Heiko Paulheim et al.)

Stay tuned and check Twitter, Facebook and our Website or subscribe to our Newsletter for latest news and information.

The DBpedia Organizing Team


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‘Knowledge Graphs in Action’ online event on Oct 6, 2020

Tuesday, July 14, 2020 - 2:43pm

Due to current circumstances, the SEMANTiCS Onsite Conference 2020 had, unfortunately, to be postponed till September 2021. To bridge the gap until 2021, DBpedia, PLDN and EuroSDR will organize a SEMANTiCS satellite event online, on October 6, 2020. We set up an exciting themed program around ‘Knowledge Graphs in Action: DBpedia, Linked Geodata and Geo-information Integration’.

This new event is a combination of two already existing ones: the DBpedia Community Meeting, which is regularly held as part of the SEMANTiCS, and the annual Spatial Linked Data conference organised by EuroSDR and the Platform Linked Data Nederland. We fused both together and as a bonus, we added a track about Geo-information Integration hosted by EuroSDR. For the joint opening session, we recruited four amazing keynote speakers to kick the event off.    

Highlights of the Knowledge Graph in Action event

– Hackathon (starts 2 weeks earlier)

– Keynote by Carsten Hoyer-Click, German Aerospace Center

– Keynote by Marinos Kavouras, National Technical University of Athens

– Keynote by Peter Mooney, Maynooth University

– Spatial Linked Data Country Session

– DBpedia Chapter Session

– Self Service GIS Session

– DBpedia Showcase Session

Quick Facts

– Web URL: https://wiki.dbpedia.org/meetings/KnowledgeGraphsInAction

– When: October 6, 2020

– Where: The conference will take place fully online.

Schedule

– Please check the schedule for the upcoming Knowledge Graphs in Action event here: https://wiki.dbpedia.org/meetings/KnowledgeGraphsInAction  

Registration 

– Attending the conference is free. Registration is required though. Please get in touch with us if you have any problems during the registration stage. Register here to be part of the meeting: https://wiki.dbpedia.org/meetings/KnowledgeGraphsInAction 

Organisation

– Benedicte Bucher, University Gustave Eiffel, IGN, EuroSDR

– Erwin Folmer, Kadaster, University of Twente, Platform Linked Data Netherlands

– Rob Lemmens, University of Twente

– Sebastian Hellmann, AKSW/KILT, DBpedia Association

– Julia Holze, DBpedia Association

Don’t think twice and register now! Join the Knowledge Graph in Action event on October 6, 2020 to catch up with the latest research results and developments in the Semantic Web Community. Register here and meet us and other SEMANTiCS enthusiasts.

For latest news and updates check Twitter, LinkedIn, the DBpedia blog and our Website or subscribe to our newsletter.

We are looking forward to meeting you online!

Julia

on behalf of the DBpedia Association

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DBpedia Workshop at LDAC

Thursday, June 25, 2020 - 11:31am

More than 90 DBpedia enthusiasts joined the DBpedia Workshop colocated with LDAC2020

On June 19, 2020 we organized a DBpedia workshop co-located with the LDAC workshop series to exchange knowledge regarding new technologies and innovations in the fields of Linked Data and Semantic Web. This workshop series provides a focused overview on technical and applied research on the usage of Semantic Web, Linked Data and Web of Data technologies for the architecture and construction domains (design, engineering, construction, operation, etc.). The workshop aims at gathering researchers, industry stakeholders, and standardization bodies of the broader Linked Building Data (LBD) community.

First and foremost, we would like to thank the LDAC committee for hosting our virtual meeting and many thanks to Beyza Yaman, Milan Dojchinovski, Johannes Frey and Kris McGlinn for organizing and chairing the DBpedia workshop. 

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

Opening & Keynote 

The first virtual DBpedia meeting was opened with a keynote presentation ‘{RDF} Data quality assessment – connecting the pieces’ by Dimitris Kontokostas (diffbot, US). He gave an overview on the latest developments and achievements around Data Quality. His presentation was focused on defining data quality and identification of data quality issues.  

Sebastian Hellmann gave a brief overview of DBpedia’s history. Furthermore, he presented the updated DBpedia Organisational architecture, including the vision of the new DBpedia chapters and benefits of the DBpedia membership.

Shortly after,  Milan Dojchinovski (InfAI/CTU in Prague) gave a presentation on  ‘Querying and Integrating (Architecture and Construction) Data with DBpedia’. ‘The New DBpedia Release Cycle’ was introduced by Marvin Hofer (InfAI). Closing the Showcase Session, Johannes Frey, InfAI, presented the Databus Archivo and demonstrated the downloading process with the DBpedia Databus

For further details of the presentations follow the links to the slides.

  • Keynote: {RDF} Data quality assessment – connecting the pieces, by Dimitris Kontokostas, diffbot, US (slides)
  • Overview of DBpedia Organisational Architecture, by Sebastian Hellmann, Julia Holze, Bettina Klimek, Milan Dojchinovski, INFAI / DBpedia Association (slides)
  • Querying and Integrating (Architecture and Construction) Data with DBpedia by Milan Dojchinovski, INFAI/CTU in Prague (slides)
  • The New DBpedia Release Cycle by Marvin Hofer and Milan Dojchinovski, INFAI (slides)
  • Databus Archivo and Downloading with the Databus by Johannes Frey, Fabian Goetz and Milan Dojchinovski, INFAI (slides)

Geospatial Data & DBpedia Session

After the opening session we had the Geospatial Data & DBpedia Session. Milan Dojchinovski (InfAI/CTU in Prague) chaired this session with three very stimulating talks. Hereafter you will find all presentations given during this session:

  • Linked Geospatial Data & Data Quality by Wouter Beek, Triply Ltd. (slides)
  • Contextualizing OSi’s Geospatial Data with DBpedia by Christophe Debruyne, Vrije Universiteit Brussel and ADAPT at Trinity College Dublin
  • Linked Spatial Data: Beyond The Linked Open Data Cloud by Chaidir A. Adlan, The Deutsche Gesellschaft für Internationale Zusammenarbeit GmbH (slides)

Data Quality & DBpedia Session

The first online DBpedia workshop also covered a special data quality session. Johannes Frey (InfAI) chaired this session with three very stimulating talks. Hereafter you will find all presentations given during this session:

  • SeMantic AnsweR Type prediction with DBpedia – ISWC 2020 Challenge by Nandana Mihindukulasooriya, MIT-IBM Watson AI Lab (slides)
  • RDF Doctor: A Holistic Approach for Syntax Error Detection and Correction of RDF Data by Ahmad Hemid, Fraunhofer IAIS (slides)
  • The Best of Both Worlds: Unlocking the Power of (big) Knowledge Graphs with SANSA by Gezim Sejdiu,  Deutsche Post DHL Group and University of Bonn (slides)
  • Closing words by the workshop organizers

In case you missed the event, all slides and presentations are also available on the DBpeda workshop website. Further insights, feedback and photos about the event are available on Twitter (#DBpediaDay hashtag).

We are now looking forward to our first DBpedia Stack tutorial, which will be held online on July 1st, 2020. Over the last year, the DBpedia core team has consolidated a great amount of technology around DBpedia. The tutorial primarily targets developers (in particular of DBpedia Chapters) that wish to learn how to replicate local infrastructure such as loading and hosting an own SPARQL endpoint. A core focus will also be the new DBpedia Stack, which contains several dockerized applications that are automatically loading data from the Databus. Attending the DBpedia Stack tutorial is free and will be organized online. Please register to be part of the meeting.

Stay tuned and check Twitter, Facebook and our Website or subscribe to our Newsletter for latest news and information.

Julia and Milan 

on behalf of the DBpedia Association

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GSoC2020 – Call for Contribution

Tuesday, March 10, 2020 - 3:48pm

James: Sherry with the soup, yes… Oh, by the way, the same procedure as last year, Miss Sophie?

Miss Sophie: Same procedure as every year, James.

…and we are proud of it. We are very grateful to be accepted as an open-source organization in this years’  Google Summer of Code (GSoC2020) edition, again. The upcoming GSoC2020 marks the 16th consecutive year of the program and is the 9th year in a row for DBpedia. 

We did it again – We are mentoring organization!

What is GSoC2020? 

Google Summer of Code is a global program focused on bringing student developers into open source software development. Funds will be given to students (BSc, MSc, PhD.) to work for three months on a specific task. For GSoC-Newbies, this short video and the information provided on their website will explain all there is to know about GSoC2020.

This year’s Narrative

Last year we tried to increase female participation in the program and we will continue to do so this year. We want to encourage explicitly female students to apply for our projects. That being said, we already engaged excellent female mentors to also raise the female percentage in our mentor team. 

In the following weeks, we invite all students, female and male alike, who are interested in Semantic Web and Open Source development to apply for our projects. You can also contribute your own ideas to work on during the summer. 

And this is how it works: 4 steps to GSoC2020 stardom

  1. Open source organizations such as DBpedia announce their projects ideas. You can find our project here
  2. Students contact the mentor organizations they want to work with and write up a project proposal. Please get in touch with us via the DBpedia Forum or dbpedia@infai.org as soon as possible.
  3. The official application period at GSoC starts March, 16th. Please note, you have to submit your final application not through our Forum, but the GSoC Website
  4. After a selection phase, students are matched with a specific project and a set of mentors to work on the project during the summer.

To all the smart brains out there, if you are a student who wants to work with us during summer 2020, check our list of project ideas, warm-up tasks or come up with your own idea and get in touch with us.

Application Procedure

Further information on the application procedure is available in our DBpedia Guidelines. There you will find information on how to contact us and how to appropriately apply for GSoC2020. Please also note the official GSoC 2020 timeline for your proposal submission and make sure to submit on time.  Unfortunately, extensions cannot be granted. Final submission deadline is March 31st, 2020, 8 pm, CEST.

Finally, check our website for information on DBpedia, follow us on Twitter or subscribe to our newsletter.

And in case you still have questions, please do not hesitate to contact us via praetor@infai.org.

We are thrilled to meet you and your ideas.

Your DBpedia-GSoC-Team


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