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 co-edit specifications such as SPARQL, and 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

• Did AI Crawlers Kill SPARQL Federation?
  Public Knowledge Graph infrastructure is degrading due to AI crawlers.
  13 April 2026
  

  RDF provides the basis for distributing Knowledge Graphs (KGs) across different locations, which is useful when KGs cover different data domains with varying purposes, are managed by different teams and organizations, or are exposed by different access policies. One of the most popular ways of publishing a KG is through a SPARQL endpoint, which offers queryable access. When multiple of these KGs need to be integrated, techniques such as SPARQL federation can be used. While many KGs have been available as public SPARQL endpoints, their openness is currently being challenged by the huge load that is placed on them by modern AI crawlers that power LLMs. Recently, public SPARQL endpoints have started putting in place stricter usage restrictions to avoid going down under this increased server load. While these restrictions limit the range of SPARQL queries that can be executed over them, it becomes especially problematic for SPARQL federated queries, which often involves sending multiple smaller queries to endpoints in a short timeframe.

• The cost of modularity in SPARQL
  How much do modularity and decentralization conflict with centralized speed?
  22 April 2025
  

  The JavaScript-based Comunica SPARQL query engine is designed for querying over decentralized environments, e.g. through federation and link traversal. In addition, it makes use of a modular architecture to achieve high flexibility for developers. To determine the impact of these design decisions, and to be able to put the base level performance of Comunica in perspective, I compared its performance to state-of-the-art centralized SPARQL engines in terms of querying over centralized Knowledge Graphs. Results show that Comunica can closely match the performance of state-of-the-art SPARQL query engines, despite having vastly different optimization criteria.

Highlighted publications

1. Conference Link Traversal Query Processing over Decentralized Environments with Structural Assumptions
   

   1. Ruben Taelman0
   2. Ruben Verborgh1

   In Proceedings of the 22nd International Semantic Web Conference (2023) To counter societal and economic problems caused by data silos on the Web, efforts such as Solid strive to reclaim private data by storing it in permissioned documents over a large number of personal vaults across the Web. Building applications on top of such a decentralized Knowledge Graph involves significant technical challenges: centralized aggregation prior to query processing is excluded for legal reasons, and current federated querying techniques cannot handle this large scale of distribution at the expected performance. We propose an extension to Link Traversal Query Processing (LTQP) that incorporates structural properties within decentralized environments to tackle their unprecedented scale. In this article, we analyze the structural properties of the Solid decentralization ecosystem that are relevant for query execution, we introduce novel LTQP algorithms leveraging these structural properties, and evaluate their effectiveness. Our experiments indicate that these new algorithms obtain accurate results in the order of seconds, which existing algorithms cannot achieve. This work reveals that a traversal-based querying method using structural assumptions can be effective for large-scale decentralization, but that advances are needed in the area of query planning for LTQP to handle more complex queries. These insights open the door to query-driven decentralized applications, in which declarative queries shield developers from the inherent complexity of a decentralized landscape. 2023
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2. Conference Comunica: a Modular SPARQL Query Engine for the Web
   

   1. Ruben Taelman0
   2. Joachim Van Herwegen1
   3. Miel Vander Sande2
   4. Ruben Verborgh3

   In Proceedings of the 17th International Semantic Web Conference (2018) Query evaluation over Linked Data sources has become a complex story, given the multitude of algorithms and techniques for single- and multi-source querying, as well as the heterogeneity of Web interfaces through which data is published online. Today’s query processors are insufficiently adaptable to test multiple query engine aspects in combination, such as evaluating the performance of a certain join algorithm over a federation of heterogeneous interfaces. The Semantic Web research community is in need of a flexible query engine that allows plugging in new components such as different algorithms, new or experimental SPARQL features, and support for new Web interfaces. We designed and developed a Web-friendly and modular meta query engine called Comunica that meets these specifications. In this article, we introduce this query engine and explain the architectural choices behind its design. We show how its modular nature makes it an ideal research platform for investigating new kinds of Linked Data interfaces and querying algorithms. Comunica facilitates the development, testing, and evaluation of new query processing capabilities, both in isolation and in combination with others. 2018
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3. Journal Triple Storage for Random-Access Versioned Querying of RDF Archives
   

   1. Ruben Taelman0
   2. Miel Vander Sande1
   3. Joachim Van Herwegen2
   4. Erik Mannens3
   5. Ruben Verborgh4

   In Journal of Web Semantics (2018) When publishing Linked Open Datasets on the Web, most attention is typically directed to their latest version. Nevertheless, useful information is present in or between previous versions. In order to exploit this historical information in dataset analysis, we can maintain history in RDF archives. Existing approaches either require much storage space, or they expose an insufficiently expressive or efficient interface with respect to querying demands. In this article, we introduce an RDF archive indexing technique that is able to store datasets with a low storage overhead, by compressing consecutive versions and adding metadata for reducing lookup times. We introduce algorithms based on this technique for efficiently evaluating queries at a certain version, between any two versions, and for versions. Using the BEAR RDF archiving benchmark, we evaluate our implementation, called OSTRICH. Results show that OSTRICH introduces a new trade-off regarding storage space, ingestion time, and querying efficiency. By processing and storing more metadata during ingestion time, it significantly lowers the average lookup time for versioning queries. OSTRICH performs better for many smaller dataset versions than for few larger dataset versions. Furthermore, it enables efficient offsets in query result streams, which facilitates random access in results. Our storage technique reduces query evaluation time for versioned queries through a preprocessing step during ingestion, which only in some cases increases storage space when compared to other approaches. This allows data owners to store and query multiple versions of their dataset efficiently, lowering the barrier to historical dataset publication and analysis. 2018
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Latest publications

1. Demo Client-Driven Offline-First RDF 1.2 using OR-Sets
   

   1. Jitse De Smet0
   2. Ruben Taelman1

   In International Conference on Web Engineering (2026) As autonomous agents increasingly write to shared RDF knowledge graphs concurrently, especially in the context of decentralized data ecosystems, principled conflict resolution becomes critical. Existing RDF CRDT approaches either require dedicated infrastructure or introduce consistency boundary problems when storing bookkeeping across multiple resources. We instantiate the state-based OR-Set over RDF 1.2 triple terms — unlike prior work, retaining all bookkeeping within a single dataset without additional infrastructure — and demonstrate a proof-of-concept datastore wrapper to use in query engines, enabling agents to query and update a conflict-free knowledge graph via standard SPARQL, unaware of the underlying merge machinery. Future work will investigate constraint-aware merge semantics for RDF CRDTs. 2026
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2. Conference Traqula: Providing a Foundation for The Evolving SPARQL Ecosystem Through Modular Query Parsing, Transformation, and Generation
   

   1. Jitse De Smet0
   2. Ruben Taelman1

   In Proceedings of the 23rd Extended Semantic Web Conference (2026) SPARQL engines continue to diverge in the versions and language extensions they support. With SPARQL 1.2 nearing completion and the working group’s plans toward future maintenance, this divergence is likely to grow. As a result, language tools that aim to support multiple SPARQL versions and dialects face increasing maintenance costs. Furthermore, areas such as SPARQL federation become harder to manage. To address these challenges, we introduce Traqula, a modular TypeScript-based framework for parsing, transforming, and generating SPARQL queries. This article presents Traqula’s architecture and its builder-based dependency-injection design, and we show how these components provide modular support for SPARQL 1.1 and 1.2 parsing and generation. Traqula enables round-tripping, supports generic algebraic and AST transformations, and delivers significantly faster parsing compared to current JavaScript-based SPARQL parsing. Traqula’s modular architecture enables flexible experimentation for researchers, and it is production-ready thanks to extensive testing and modern development techniques. Looking forward, Traqula lays the groundwork for supporting additional query languages, developing generic rewriting modules for SPARQL federation engines, and building robust tooling for an increasingly diverse SPARQL ecosystem. 2026
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3. Poster From VCF to RDF: RML-Based Conversion Approaches for the Semantic Representation of Variant Data
   

   1. Elias Crum0
   2. Bart Buelens1
   3. Gokhan Ertaylan2
   4. Ruben Taelman3

   In Proceedings of the 17th International SWAT4HCLS Conference (2026) Representing Variant Call Format (VCF) data using the Resource Description Framework (RDF) offers benefits in interoperability, integration with other biomedical datasets, and selective privacy protections. Due to complexities of the data represented in VCF files, conversion of VCF to RDF poses challenges, especially concerning complex, heterogeneous data fields. Here, we propose converting VCF files to serialized RDF using the RML mapping language and established genomic data ontologies. Such a methodology will demonstrate the feasibility of an RML-based approach and inform a more FAIR, machine-actionable representation strategy for representing VCF data that is compatible with semantic data privacy policies and useful in both clinical and academic domains. 2026
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4. Journal Genomic sequence data sharing for clinical practice: A scoping review
   

   1. Elias Crum0
   2. Ruben Taelman1
   3. Bart Buelens2
   4. Gokhan Ertaylan3

   In Computers in Biology and Medicine (2026) A key barrier to scaling genomic medicine is sharing patient genomic data. This study assesses current genomic data sharing approaches, infrastructure, and guidelines, while incorporating insights from national initiatives and industry to ensure broad relevance. We aim to provide a foundation for dialogue by highlighting current challenges and barriers while promoting actionable standards and future points of emphasis. Our analysis uses Arksey & O’Malley’s scoping review framework to survey peer-reviewed articles, gray literature, national genomics initiatives, and corporate strategies to address four questions revolving around what genome data sharing approaches exist in: 1. Clinical-care, 2. Research, 3. National genome initiatives, and 4. Corporations. We identified 55 studies, separated them into groups, and determined 7 core components of an implementable technology. Notably, the studies included 15 clinical genome sharing implementations, 9 research-focused frameworks, and 13 ethical/legal guidelines. We also analyzed 57 active national genome initiatives and 20 major genomics companies. We found implementations for clinical genomic data sharing exist, yet scalability and widespread adoption remain limited. We identify scalability, clinical versus research-grade infrastructure requirements, and genomic medicine maturity as main challenges to overcome and suggest 4 steps that will encourage a unified path forward. Our discussion aims to facilitate discourse and catalyze future genomic data sharing system innovation. 2026
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5. Journal Expressive Querying and Scalable Management of Large RDF Archives
   

   1. Olivier Pelgrin0
   2. Ruben Taelman1
   3. Luis Galárraga2
   4. Katja Hose3

   In Semantic Web Journal (2025) The proliferation of large and ever-growing RDF datasets has sparked a need for robust and performant RDF archiving systems. In order to tackle this challenge, several solutions have been proposed throughout the years, including archiving systems based on independent copies, time-based indexes, and change-based approaches. In recent years, modern solutions combine several of the above mentioned paradigms. In particular, aggregated changesets of time-annotated triples have showcased a noteworthy ability to handle and query relatively large RDF archives. However, such approaches still suffer from scalability issues, notably at ingestion time. This makes the use of these solutions prohibitive for large revision histories. Furthermore, applications for such systems remain often constrained by their limited querying abilities, where SPARQL is often left out in favor of single triple-pattern queries. In this paper, we propose a hybrid storage approach based on aggregated changesets, snapshots, and multiple delta chains that additionally provides full querying SPARQL on RDF archives. This is done by interfacing our system with a modified SPARQL query engine. We evaluate our system with different snapshot creation strategies on the BEAR benchmark for RDF archives and showcase improvements of up to one order of magnitude in ingestion speed compared to state-of-the-art approaches, while keeping competitive querying performance. Furthermore, we demonstrate our SPARQL query processing capabilities on the BEAR-C variant of BEAR. This is, to the best of our knowledge, the first openly-available endeavor that provides full SPARQL querying on RDF archives. 2025
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