About

Who are we?

IDLab is a research group of imec, embedded in Ghent University (departments IBCN & DSLab) & University of Antwerp, performing fundamental & applied research on internet technology & data science. IDLab has world-leading expertise in the entire data value chain, from data acquisition, enrichment, storage, representation, to mining and learning from data, visualization & valorization. The Knowledge on Web-Scale team (KNoWS) focuses on integrating and publishing various datasets on the Web.

The Knowledge on Web Scale (KNoWS) research unit crosses two groups within IDLab, i.e. DSLab & IBCN. KNoWS is led by Prof. Verborgh, Prof. Colpaert & Prof. Ongenae and consists of 5 post-docs & 27 PhD students. KNoWS has a long-standing track record in Semantic Web research. KnoWS covers the full data management ecosystem to generate Linked Data (e.g RML), publish these using a Web API (e.g. LDF), enable feedback (e.g. Solid), and query the data while performing reasoning (e.g. N3, MASSIF, Roxi & Comunica). KNoWS is a world top-3 Semantic Web research lab, invaluable to the Solid project as they spearhead – together with MIT & Sir Tim Berners-Lee – in Solid protocols and Solid-related technical research. IDLab has a history of participating in W3C standards, e.g. Media Fragments, PROV, LDES, Solid, N3 & Linked Data Platform.

The KNoWS research group is led by Prof. Dr. Ruben Verborgh, Prof. Dr. Pieter Colpaert, and Prof. Dr. Femke Ongenae, and is regarded as a world-class research group in the Semantic Web domain. See our list of publications.

Teams

The KNowledge on Web Scale (KNoWS) group of IDLab is an experienced team of creative researchers in advanced data technologies. Our mission involves enabling optimal flows of public and protected data between different parties, and our ultimate goal is for data to impact people’s lives positively in ways they choose themselves.

Expertise and technologies

We apply the following expertise and technologies to data problems within and across multiple domains:

  • We apply Linked Data and Semantic Web technologies (RDF, RDFS, OWL…) to model complex federated and decentralized scenarios, in which data never resides in a single place.
  • We design, implement, and evaluate reasoning (N3, OWL, ...) & processing algorithms (federated AI, aggregations, ...) on static datasets as well as data streams, in order to validate and draw conclusions from semantic Linked Data, and for detection and reaction to time-critical insights at scale.
  • We design, implement, and evaluate Web APIs (HTTP, protocols, REST, ...) for the exchange of structured data, both at a theoretical–conceptual level and a practical level.
  • We design, implement, and evaluate scalable query algorithms (SPARQL, GraphQL, RSP-QL, ...) for structured data in decentralized environments.
  • We design, implement, and evaluate synchronization, replication, and summarization algorithms for large-scale distributed data ecosystems.
  • We transform and enrich data (RML, FnO) to bridge gaps between heterogeneous systems and data architectures.
  • We design, implement, and evaluate data usage control and policy algorithms (ODRL, DPV), bridging between the technological and legal domains.
  • We develop standards-based solutions for personal data vaults (Solid) and associated specifications for authentication (OIDC) and authorization (UMA).

Focus domains

In addition to domain-agnostic data technologies, we have an extensive portfolio of applied research and development in domains such as:

  • Preventive healthcare & homecare
  • Transport and mobility
  • Logistics
  • Cultural Heritage
  • Water reuse
  • E-government
  • Supply chain
  • Data governance
  • Building management
  • Media
  • Industry 4.0 / 5.0
  • ...

Activities and services

  • Fundamental, strategic, and applied research
  • Contract-based research with academic and industrial partners
  • Scientific consultancy for industrial and governmental partners
  • Specification and standardization (W3C, SEMIC, IETF…)

Work with us

Our world-class team features renowned experts, who collectively represent in-depth knowledge spanning over 500 peer-reviewed scientific publications.