Tag Archives: DBpedia Day

SEMANTiCS Interview: Dan Weitzner

As the upcoming 14th DBpedia Community Meeting, co-located with SEMANTiCS 2019 in Karlsruhe, Sep 9-12, is drawing nearer, we like to take that opportunity to introduce you to our DBpedia keynote speakers.

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.

Dan Weitzner

1. 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.

2. 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.

3. 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.

4. 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.

5. 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.

6. 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