Tag Archives: DBpedia Member

A year with DBpedia – Retrospective Part 2/2020

This is the final part of our journey through 2020. In the previous blog post we already presented DBpedia highlights, events and tutorials. Now we want to take a deeper look at the second half of 2020 and give an outlook for 2021.

DBpedia Autumn Hackathon and the KGiA Conference

From September 21st to October 1st, 2020 we organized the first Autumn Hackathon. We invited all community members to join and contribute to this new format. You had the chance to experience the latest technology provided by the DBpedia Association members. We hosted special member tracks, a Dutch National Knowledge Graph Track and a track to improve DBpedia. Results were presented at the final hackathon event on October 5, 2020. We uploaded all contributions on our Youtube channel. Many thanks for all your contributions and invested time!

The Knowledge Graphs in Action event

Chairs open the KGiA event on October 6, 2020.
Opening the KGiA event

The SEMANTiCS Onsite Conference 2020 had to be postponed till September 2021. To bridge the gap until 2021, we took the opportunity to organize the Knowledge Graphs in Action 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, which is regularly held as part of the SEMANTiCS, and the annual Spatial Linked Data conference organised by EuroSDR and the Platform Linked Data Netherlands. We glued it together and as a bonus we added a track about Geo-information Integration organized by EuroSDR. As special joint sessions we presented four keynote speakers. More than 130 knowledge graph enthusiasts joined the KGiA event and it was a great success for the organizing team. Do you miss the event? No problem! We uploaded all recorded sessions on the DBpedia youtube channel.

KnowConn Conference 2020

Our CEO, Sebastian Hellmann, gave the talk ‘DBpedia Databus – A platform to evolve knowledge and AI from versioned web files’ on December 2, 2020 at the KnowledgeConnexions Online Conference. It was a great success and we received a lot of positive and constructive feedback for the DBpedia Databus. If you missed his talk and looking for Sebastians slides, please check here: http://tinyurl.com/connexions-202

DBpedia Archivo – Call to improve the web of ontologies

Search bar to inspect an archived ontology - DBpedia Archivo
DBpedia Archivo

On December 7, 2020 we introduced the DBpedia Archivo – an augmented ontology archive and interface to implement FAIRer ontologies. Each ontology is rated with 4 stars measuring basic FAIR features. We would like to call on all ontology maintainers and consumers to help us increase the average star rating of the web of ontologies by fixing and improving its ontologies. You can easily check an ontology at https://archivo.dbpedia.org/info. Further infos on how to help us are available in a detailed post on our blog. 

Member features on the blog

At the beginning of November 2020 we started the member feature on the blog. We gave DBpedia members the chance to present special products, tools and applications. We published several posts in which DBpedia members, like Ontotext, GNOSS, the Semantic Web Company, TerminusDB or FinScience shared unique insights with the community. In the beginning of 2021 we will continue with interesting posts and presentations. Stay tuned!

We do hope we will meet you and some new faces during our events next year. The DBpedia Association wants to get to know you because DBpedia is a community effort and would not continue to develop, improve and grow without you. We plan to have meetings in 2021 at the Knowledge Graph Conference, the LDK conference in Zaragoza, Spain and the SEMANTiCS conference in Amsterdam, Netherlands.

Happy New Year to all of you! Stay safe and check Twitter, LinkedIn and our Website or subscribe to our Newsletter for the latest news and information.

Yours,

DBpedia Association

Ontotext GraphDB on DBpedia

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