Personal Homepage of Wouter Beek

I'm a post-doctoral researcher at VU University Amsterdam (VUA) and co-founder of Triply.

As part of my research, I have co-developed the LOD Laundromat, LOD Search, and sameAs.cc.

I am interested in the Semantic Web as a platform for knowledge-intensive applications, the deployment of large-scale knowledge bases for innovative reuse, and the interaction between Web semantics and pragmatics, including the empirical study of semantics.

Introduction into Knowledge Graphs

This presentation introduces the idea of publishing an organization's information assets in an integrated Knowledge Graph. It will give examples of real-world Knowledge Graphs and their productive use.

Adding 3D Visualization to the SPARQL Query Loop (August 30^th)

In presentation we explain how 3D visualization can be used to visualize SPARQL result sets. The benefit of such a visualization is that it allows geo-spatial and statistical results to be interpreted in a more natural and easy way.
This presentation was held at the Free and Open Source Software for Geo (FOSS4G) Conference 2018.

Presentation about the LOD Laundromat, a large-scale Linked Data crawling and cleaning infrastructure.

The ‘K’ in ‘Semantic Web’ Stands for ‘Knowledge’ (June 19^th)

These are the introductory slides to the defense of my PhD thesis The ‘K’ in ‘Semantic Web’ Stands for ‘Knowledge’.

Near Sameness is Somewhat the Same As Sameness

Presentation about the owl:sameAs property and the https://sameas.cc resource and web service. Presented at ESWC 2018; winner of the Best Resource Paper Award.

nlGis: A Use Case in Linked Historic Geodata (June 3^rd, 2018)

Meaning on the Web

Lecture in the Knowledge Representation on the Web course.

This presentation covers various aspects of Linked Data Quality.

Empirical Semantics

Presentation about Empirical Semantics, a new approach towards the study of meaning that uses empirical experiments over Big Semantics Web Data.

Semantics of Knowledge Graphs

This presentation introduces the formalization of meaning within a Knowledge Graph. It follows Semantic Web standards in order to determine the automatically assign meaning to data items.