Hi!
I'm Ruben Taelman, a Web postdoctoral researcher at IDLab,
with a focus on decentralization, Linked Data publishing and querying.
My goal is to make data accessible for everyone by providing
intelligent infrastructure and algorithms for data publication and retrieval.
To support my research, I develop various open source JavaScript libraries such as streaming RDF parsers and the Comunica engine to query Linked Data on the Web.
As this website itself contains Linked Data, you can query it live with Comunica.
Have a look at my publications or projects
and contact me if any of those topics interest you.
Latest blog posts
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5 rules for open source maintenance
Guidelines for publishing and maintaining open source projects.
Thanks to continuing innovation of software development tools and services, it has never been easier to start a software project and publish it under an open license. While this has lead to the availability of a huge arsenal of open source software projects, the number of qualitative projects that are worth reusing is of a significantly smaller order of magnitude. Based on personal experience, I provide five guidelines in this post that will help you to publish and maintain highly qualitative open-source software.
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Who says using RDF is hard?
A brief overview on RDF and Linked Data development in JavaScript.
The Linked Data ecosystem and RDF as its graph data model have been around for many years already. Even though there is an increasing interest in knowledge graphs, many developers are scared off by RDF due to its reputation of being complicated. In this post, I will show some concrete examples on how RDF can be used in JavaScript applications, to illustrate that RDF is actually pretty easy to work with if you use the right tools.
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A story of streaming RDF parsers
How I implemented streaming JSON-LD and RDF/XML parsers in JavaScript.
Multiple serialization formats are currently being recommended by the W3C to represent RDF. JSON-LD and RDF/XML are examples of RDF serializations that are respectively based on the JSON and XML formats. The ability to parse RDF serializations in a streaming way offers many advantages, such as handling huge documents with only a limited amount of memory, and processing elements as soon as they are parsed. In this post, I discuss the motivation behind my streaming parser implementations for JSON-LD and RDF/XML, their architecture, and I show some live examples.
Highlighted publications
- Conference Comunica: a Modular SPARQL Query Engine for the WebMore
In Proceedings of the 17th International Semantic Web Conference - Journal Triple Storage for Random-Access Versioned Querying of RDF ArchivesMore
In Journal of Web Semantics - Journal Generating Public Transport Data based on Population Distributions for RDF BenchmarkingMore
In Semantic Web Journal - Conference Continuous Client-Side Query Evaluation over Dynamic Linked DataMore
In The Semantic Web: ESWC 2016 Satellite Events, Heraklion, Crete, Greece, May 29 – June 2, 2016, Revised Selected Papers
Latest publications
- Demo PROV4ITDaTa: Transparent and direct transfer of personal data to personal storesMore
In WWW2021, the International World Wide Web Conference - Journal Semantic micro-contributions with decentralized nanopublication servicesMore
In PeerJ Computer Science - Workshop Optimizing Approximate Membership Metadata in Triple Pattern Fragments for Clients and ServersMore
In Proceedings of the 13th International Workshop on Scalable Semantic Web Knowledge Base Systems - Workshop RDF Test Suite: Improving Developer Experience for Building Specification-Compliant LibrariesMore
In Proceedings of the 1st Workshop on The Semantic Web in Practice: Tools and Pedagogy - Conference LDflex: a Read/Write Linked Data Abstraction for Front-End Web DevelopersMore
In Proceedings of the 19th International Semantic Web Conference