Wouter Maroy
Lead, Enterprise Architecture Cyber & Digital Transformation Division
Belgium
Summary
👤
Senior🎓
Top SchoolWouter Maroy is a Lead in Enterprise Architecture within NATO’s Cyber & Digital Transformation Division, bringing a decade of experience bridging cloud-native engineering and strategic architecture. With a strong computer science background from Ghent University and hands-on roots in backend development, he has moved from cloud engineering at Deloitte to shaping enterprise-wide architecture and policy at NATO. He contributes to open-source projects like DBpedia’s extraction framework, enhancing RML mappings to better handle dates, geo-coordinates and diverse data types—evidence of his attention to data interoperability. Known for translating research-era rigor from imec/IDLab into pragmatic cloud solutions, he combines technical depth with leadership across complex, security-sensitive environments. Based in Belgium, he blends consultant curiosity with operational authority to deliver scalable, auditable cloud architectures.
10 years of coding experience
7 years of employment as a software developer
Master of Science (M.Sc.) Computer Science Engineering, Master of Science (M.Sc.) Computer Science Engineering at Ghent UniversityWetenschappen-Wiskunde, Wetenschappen-Wiskunde at Sint-Bernarduscollege Oudenaarde
Dutch, English
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (3)
scala10
data-extraction9
jena8
Programming languages (6)
Github contributions (5)
dbpedia/extraction-framework
Jun 2016 - Sep 2017
The software used to extract structured data from Wikipedia
Role in this project:
Back-end Developer
Back-end DeveloperContributions:249 commits, 3 PRs, 88 pushes in 1 year 3 months
Contributions summary:Wouter primarily focused on updating the RMLModelMapper within the extraction-framework repository. Their contributions centered around adding and modifying RML mappings, specifically for simple property mappings, date interval mappings, and geo-coordinates. The updates involved creating and connecting predicate object maps, incorporating unit handling, and refining the mapping processes for different data types, suggesting a focus on enriching the framework with RML capabilities. These changes demonstrate a focus on enabling the framework to handle diverse data extraction scenarios.
pythonstructured-datastructuredwikipedia
FnOio/dbpedia-parsing-functions-scala
Dec 2016 - Aug 2017
Contributions:22 commits, 15 pushes, 3 branches in 8 months
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