About the mission
We are looking for a Semantic Expert - Architect to join our development team for semantic applications. The ideal candidate will have extensive experience with linked data technologies and a strong background in developing semantic microservices. This role offers the opportunity to work in a dynamic environment focused on improving digital services for local authorities.
Read the full description
Overview
With the Local Decisions program as Linked Open Data, we have introduced a completely new technique for data sharing within and between local authorities and other levels of government. Meanwhile, an ecosystem around 'local authorities as Linked Open Data' has emerged, upon which various actors and applications are based: https://abb-vlaanderen.gitbook.io/abb/v/master/#een-semantisch-ecosysteem.Within this ecosystem, we have built various open-source semantic applications for end-users, backend microservices that query and edit the semantic data, and components are being developed that require extensive knowledge of the semantic models, data querying, and code. We also actively focus on design and user experience to ensure that the applications are attractively and user-friendly designed and maximally meet the needs of users. More information about our vision and product portfolio can be found at: https://abb-vlaanderen.gitbook.io/abb/
Due to investments made by the Flemish Government through Flemish Resilience, numerous projects are currently underway where governments, especially local authorities, want to transform their operations and services to be more citizen-oriented and efficient by maximizing the possibilities of smart technologies. These projects almost always face the challenge of "how can we keep information about local products and services up-to-date so that citizens and organizations can experience smooth digital services?"
This is precisely the core of what we want to solve with our LBLOD ecosystem. We aim to widely implement this proven method and technology within the ongoing wave of digitization.
Do Linked Data and the development of semantic applications hold no secrets for you? Would you like to work in a dynamic environment that builds an important information hub for Flanders? Then you might be the perfect candidate to be part of our development team for our semantic applications.
Key Responsibilities
Proven experience with the implementation of semantic (linked data) technology
Proven experience with Ember
Proven experience with Github
Proven experience in developing and deploying components using Linux containers and Docker
Proven experience in developing semantic microservices
Proven experience with mu.semte.ch
Proven experience with single-page apps
Proven experience with triple stores such as Virtuoso
Proven experience with the technology in question or a similar technology
Proven expertise in linked-data technology (sparql, rdf, rdfa, json-ld, LDES...)
Intrinsically motivated and engaged with the intergovernmental and transversal context of the agency and stakeholders (please upload a document with motivation)
Proven experience working in an advanced scrum team (ideally within SAFE operation)
Skills & Experience
Higher education (Master or Bachelor) with a technical/engineering background or equivalent through experience with ICT technology for which expertise is requested
Insight into commonly used vocabularies and ontologies
Proven experience with digitization projects within the Flemish government and/or local authorities
Languages
Language requirement: Dutch at European CEFR - level C2
Additional Info
Preferred start date: 01/03/2026
Preferred end date: 31/07/2026
Number requested: 1
Assignment type: Framework contract 2022 - 2027 (Lot 1)
Department: Lot 1 (P1)
Remote work possible: Yes
For all profiles, internships, academic/study experience, and hobby projects can also be submitted as relevant experience
ABB provides for an annual indexing subject to prior agreement.
What you'll do
- Proven experience with the implementation of semantic (linked data) technology
- Proven experience with Ember
- Proven experience with Github
- Proven experience in developing and deploying components using Linux containers and Docker
- Proven experience in developing semantic microservices
- Proven experience with mu.semte.ch
- Proven experience with single-page apps
- Proven experience with triple stores such as Virtuoso
- Proven experience with the technology in question or a similar technology
- Proven expertise in linked-data technology (sparql, rdf, rdfa, json-ld, LDES...)
- Intrinsically motivated and engaged with the intergovernmental and transversal context of the agency and stakeholders (please upload a document with motivation)
- Proven experience working in an advanced scrum team (ideally within SAFE operation)
What we're looking for
- Proven experience with the implementation of semantic (linked data) technology
- Proven experience with Ember
- Proven experience with Github
- Proven experience in developing and deploying components using Linux containers and Docker
- Proven experience in developing semantic microservices
- Proven experience with mu.semte.ch
- Proven experience with single-page apps
- Proven experience with triple stores such as Virtuoso
- Proven experience with the technology in question or a similar technology
- Proven expertise in linked-data technology (sparql, rdf, rdfa, json-ld, LDES...)
- Intrinsically motivated and engaged with the intergovernmental and transversal context of the agency and stakeholders (please upload a document with motivation)
- Proven experience working in an advanced scrum team (ideally within SAFE operation)
- Higher education (Master or Bachelor) with a technical/engineering background or equivalent through experience with ICT technology for which expertise is requested
- Insight into commonly used vocabularies and ontologies
- Proven experience with digitization projects within the Flemish government and/or local authorities
Skills
- Linked Data
- Ember
- Github
- Linux Containers
- Docker
- Semantic Microservices
- Triple Stores
- SPARQL