First and foremost, we would like to thank the Institute for Applied Informatics for supporting our community and many thanks to the VU University Amsterdam and the SEMANTiCS organisation team for hosting this year’s DBpedia Day.  

Opening of the DBpedia Day

Our CEO, Sebastian Hellmann, opened the DBpedia Day with an update about the DBpedia Databus and DBpedia members. He presented the huge and diverse network DBpedia has built up in the last 13 years. Afterwards, Maria-Esther Vidal, TIB, completed the opening session with her keynote “Enhancing Linked Data Trustability and Transparency through Knowledge-driven Data Ecosystems”. If you would like to get more insights, please find both slide decks here.  

Member Presentation Session 

Dennis Diefenbach, The QA Company, started the DBpedia member presentation session with his presentation “Question Answering over DBpedia”. Shortly after,  Luke Feeney and Gavin Mendel-Gleason, TerminusDB, promoted the implementation of a cloud data mesh with a Knowledge Graph. Next, Russa Biswas, FIZ, talked about “Entity Type Prediction in DBpedia using Neural Networks”. Followed by another remote presentation by Ricardo Alonso Maturana and Susana López, Gnoss, presenting the “Didactalia Encyclopaedia”. They demonstrated a chronological, compared and contextual perspective of enriched and linked entities. 

Afterwards, Antonia Donvito from FinScience explained how they use DBpedia Spotlight-a tool for automatically annotating mentions of DBpedia resources in text, providing a solution for linking unstructured information sources to the Linked Open Data cloud through DBpedia. Kathrin Dentler, Triply, talked about “Bringing linked data to the domain expert with TriplyDB data stories”. Closing the member session, Margaret Warren, ImageSnippets, presented “Anchoring Images to Meaning Using DBpedia” live via Zoom from Florida, U.S.      

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

• “Question Answering over DBpedia” by Dennis Diefenbach, The QA Company (slides)
• Implementing a Cloud Data Mesh with a Knowledge Graph” by Luke Feeney and Gavin Mendel-Gleason, TerminusDB (slides)
• “Entity Type Prediction in DBpedia using Neural Networks” by Russa Biswas, FIZ Karlsruhe (slides)
• “Didactalia Encyclopaedia: a chronological, compared and contextual perspective of enriched and linked entities which presents a global view of human knowledge using semantic artificial intelligence” by Ricardo Alonso Maturana, GNOSS (slides)
• “DBpedia Spotlight @ FinScience: alternative data for fintech applications” by Antonia Donvito, FinScience (slides)
• “Bringing linked data to the domain expert with TriplyDB data stories” by Kathrin Dentler, Triply (slides)
• “Anchoring Images to Meaning Using DBpedia” by Margaret Warren, ImageSnippets (slides)

Ontology and NLP Sessions at the DBpedia Day

As a regular part of the DBpedia Community Meeting, we had two parallel sessions in the afternoon where DBpedians discussed most recent challenges in the context of DBpedia. Participants interested in NLP-related topics joined the NLP & DBpedia session. Milan Dojchinovski (InfAI, CTU Prague) chaired this session with four very stimulating talks. Hereafter you will find the presentations given during this session:

• “Zero-Shot Text Classification for Scholarly Data with DBpedia” by Fabian Hoppe, FIZ Karlsruhe (slides)
• “European network for Web-centred linguistic data science” by Jorge Gracia (University of Zaragoza) and Thierry Declerck, DFKI, Germany (slides)
• “Capturing the semantics of documentary evidence of humanities research” by Enrico Daga, KMi, The Open University, United Kingdom (slides)
• “NLP & DBpedia: Literature Review” by Artem Revenko, Semantic Web Company, Austria (slides)

At the same time, the DBpedia Ontology Session provided a platform for the community to discuss implementable criteria to evaluate ontologies, especially the ontology archive DBpedia Archivo. Hereafter you will find all presentations given during this session: 

• “Introduction & Motivation” by Sebastian Hellmann, InfAI/DBpedia (slides)
• “Exploiting Semantic Knowledge Graphs to enable data integration and interoperability within the Agrifood sector” by Monika Solanki, Agrimetrics (slides)
• “DBpedia Archivo” by Denis Streitmatter, InfAI/AKSW (slides)
• “FOOPS! An Ontology Pitfall Scanner for the FAIR principles” by Daniel Garijo, UPM (slides)

Diversity of DBpedia – The DBpedia Language Chapters

This year’s DBpedia Day also covered a special chapter session, chaired by Enno Meijers, KB and Dutch DBpedia Language Chapter. Two speakers presented the latest technical and organizational developments of their respective chapters. Furthermore, Johannes Frey showcased the Dutch National Knowledge Graph (DNKG). During the DBpedia Autumn Hackathon 2020 the DBpedia team worked together with a group of Dutch organizations to explore the feasibility of building a DNKG. The knowledge graph was built from a number of authoritative datasets using the DBpedia Databus approach. 

Following, you find a list of all presentations of this session: 

• “Latest enhancements in the Spanish DBpedia” by Mariano Rico, Technical University of Madrid (UPM) (slides)
• “Creating the Hungarian DBpedia using the Databus” by Andras Micsik, SZTAKI (slides)
• “Dutch National Knowledge Graph pilot” by Johannes Frey, InfAI/DBpedia Association) (slides)
• Discussion about the future of the local DBpedia chapters lead by Enno Meijers

In this DBpedia chapter session we had a closer look at the results of the DNKG pilot. Furthermore, two DBpedia language chapters (Spanish and Hungarian) presented current developments and research results. Closing this session, Enno Meijers led a discussion about the opportunities of the DBpedia Databus for creating local chapters and building (national) knowledge graphs in general.

Summing up, the DBpedia Day at the SEMANTiCS conference brought together more than 100 DBpedia enthusiasts from Europe who engaged in vital discussions about Linked Data, the DBpedia archivo as well as DBpedia use cases and services.

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

We are now looking forward to more DBpedia meetings in the next year. DBpedia will be part of the Connected Data World taking place online on December 1–3, 2021. We will organize a masterclass.

Stay safe and check Twitter or LinkedIn. Furthermore, you can subscribe to our Newsletter for the latest news and information around DBpedia.

Julia

on behalf of the DBpedia Association

The post DBpedia Day – Hallo Gemeenschap! appeared first on DBpedia Association.

September 9th, 2021 at 1pm CEST: In particular, we would like to invite you to the DBpedia Ontology session at the DBpedia Day at SEMANTiCS 2021 to discuss the future roadmap for Archivo as a Unified Semantic Ontology Space (USOS) and what the role of the DBpedia Ontology will be in the Semantic Web.

Session Topics

The session will host impulse talks with ample room for discussion. For the first time in the history of the Semantic Web, Archivo offers the possibility to create a Unified Semantic Ontology Space (USOS), a holistic view over all available ontologies. Instead of soft and fuzzy principles such as FAIR, we will discuss hard, implementable criteria to evaluate ontologies in preparation of a well-defined, measurable standard, which will ultimately yield better and reliable ontologies for industrial applications. Another topic is the central collaboration on links and mappings between ontologies to create a more dense and well-connected web of ontologies. Join the discussion and register here.

Successes and Highlights

An Exhaustive Ontology Archive

We implemented 5 discovery mechanisms that run each week. These mechanisms have proven effective to develop Archivo into one of the most exhaustive ontology archives. As of today, Archivo provides an alternative, persistent download location for 1407 ontologies. Growth has not reached a plateau, yet and it is steadily growing at a pace of 12.6 ontologies per week (6 month average). 

Community Adoption

While 1246 ontologies were automatically discovered, we also received 159 user submission (i.e. adding the Ontology URL at https://archivo.dbpedia.org/add). Archivo is also serving 90 ontology downloads on an average day (plus 640 daily downloads from major bots) and will soon provide popularity ratings. The archive can be downloaded as a whole. Note that we also keep some ontologies that are no longer available under their original URL such as: GEORSS (info, download) to allow stable operation of the Semantic Web. 

Ontology Accessibility

Archivo uses all kinds of cunning tricks to find, access and persist ontologies. Our crawlers and parsers have matured over the last year and – although we might have overlooked something – we are quite certain that the following statement holds: “If DBpedia Archivo can not process an ontology, the ontology is not retrievable or parseable, which will negatively impact all further applications”.  On the other hand, if Archivo manages to access and parse the ontology, it will be persisted for future generations (following a fair use / no abuse policy regarding size restrictions). 

Ontology Quality vs. Coverage

Besides accessibility, Archivo evaluates availability and conformity of license statements as well as consistency as a minimal baseline to assign the 4 Archivo stars. On August 16th, 2021, we can report that the web of ontology reached above 2 stars on average with 303 ★★★★, 246 ★★★☆, 18 ★★☆☆ and 836 ★☆☆☆ ontologies. Two weeks later the average fell to 1.999 stars as 4 more ontologies were discovered.  We see it as a challenge for Archivo to likewise improve the orthogonal goals of exhaustive coverage as well as high quality ontologies. We believe, however, that the system is able to accommodate both over time. 

Versioning

Ontologies are checked every 8 hours for changes. So far Archivo has archived 3713 for the 1407 ontologies. Ontology practitioners are now able to code applications to specific archived ontology versions and need not fear that major ontological changes are published under the same URL, breaking SPARQL queries and applications.  

Stay safe and check Twitter or LinkedIn. Furthermore, you can subscribe to our Newsletter for the latest news and information around DBpedia.

Sebastian Hellmann

on behalf of the DBpedia Association

The post DBpedia Archivo: 1 Year Retrospective appeared first on DBpedia Association.

Today’s post features an interview with Dan Weitzner from WPSemantix who talks about timbr-DBpedia, which we blogged about recently, as well as future trends and challenges of linked data and the semantic web.

Dan Weitzner is co-founder and Vice President of Research and Development of WPSemantix. He obtained his Bachelor of Science in Computer Science from Florida Atlantic University. In collaboration with DBpedia, he and his colleagues at WPSemantix launched timbr, the first SQL Semantic Knowledge Graph that integrates Wikipedia and Wikidata Knowledge into SQL engines.

Can you tell us something about your research focus?

WPSemantix bridges the worlds of standard databases and the Semantic Web by creating ontologies accessible in standard SQL. 

Our platform – timbr– is a virtual knowledge graph that maps existing data-sources to abstract concepts, accessible directly in all the popular Business Intelligence (BI) tools and also natively integrated into Apache Spark, R, Python, Java and Scala. 

timbr enables reasoning and inference for complex analytics without the need for costly Extract-Transform-Load (ETL) processes to graph databases.

How do you personally contribute to the advancement of semantic technologies?

We believe we have lowered the fundamental barriers to adoption of semantic technologies for large organizations who want to benefit from knowledge graph capabilities without firstly requiring fundamental changes in their database infrastructure and secondly, without requiring expensive organizational changes or significant personnel retraining.  

Additionally, we implemented the W3C Semantic Web principles to enable inference and inheritance between concepts in SQL, and to allow seamless integration of existing ontologies from OWL. Subsequently, users across organizations can do complex analytics using the same tools that they currently use to access and query their databases, and in addition, to facilitate the sophisticated query of big data without requiring highly technical expertise.  
timbr-DBpedia is one example of what can be achieved with our technology. This joint effort with the DBpedia Association allows semantic SQL query of the DBpedia knowledge graph, and the semantic integration of the DBpedia knowledge into data warehouses and data lakes. Finally, timbr-DBpedia allows organizations to benefit from enriching their data with DBpedia knowledge, combining it with machine learning and/or accessing it directly from their favourite BI tools.Which trends and challenges do you see for linked data and the semantic web?

Currently, the use of semantic technologies for data exploration and data integration is a significant trend followed by data-driven communities. It allows companies to leverage the relationship-rich data to find meaningful insights into their data. 

One of the big difficulties for the average developer and business intelligence analyst is the challenge to learn semantic technologies. Another one is to create ontologies that are flexible and easily maintained. We aim to solve both challenges with timbr.

Which application areas for semantic technologies do you perceive as most promising?

I think semantic technologies will bloom in applications that require data integration and contextualization for machine learning models.

Ontology-based integration seems very promising by enabling accurate interpretation of data from multiple sources through the explicit definition of terms and relationships – particularly in big data systems,  where ontologies could bring consistency, expressivity and abstraction capabilities to the massive volumes of data.As artificial intelligence becomes more and more important, what is your vision of AI?

I envision knowledge-based business intelligence and contextualized machine learning models. This will be the bedrock of cognitive computing as any analysis will be semantically enriched with human knowledge and statistical models.

This will bring analysts and data scientists to the next level of AI.

What are your expectations about Semantics 2019 in Karlsruhe?

I want to share our vision with the semantic community and I would also like to learn about the challenges, vision and expectations of companies and organizations dealing with semantic technologies. I will present “timbr-DBpedia – Exploration and Query of DBpedia in SQL”

The End

Visit SEMANTiCS 2019 in Karlsruhe, Sep 9-12 and find out more about timbr-DBpedia and all the other new developments at DBpedia. Get your tickets for our community meeting here. We are looking forward to meeting you during DBpedia Day.

Yours DBpedia Association

The post SEMANTiCS Interview: Dan Weitzner appeared first on DBpedia Association.