The ICAI OpenGov Lab centers its research on one core theme: artificial intelligence for open government.
To drive these advancements, the lab leverages key technical AI components, focusing primarily on:
Natural Language Processing
Machine Learning
With a commitment to explainable, and responsible AI systems.
The ICAI OpenGov Lab is dedicated to bridging the gap between technical AI research and sustainable agricultural practice.
The lab’s mission and vision are to improve and support interpretation, retrieval, and use of open government data, to increase government transparency, public trust, and ultimately democratic participation.
The impact of the lab lies in addressing the entire information-chain ecosystem by improving information culture and practices within government, and empowering citizens to engage more effectively in public discourse and decision-making.
Publishing FAIR open government data – Focuses on supply-side technologies to make government documents and structured collections findable, accessible, interoperable, and reusable.
Advanced search for open government data – Focuses on demand-side search tools to help citizens, journalists, and professionals search complex government data.
Advanced NLP for open government data – Focuses on NLP tools for summarizing, simplifying, and conversationally exploring text collections.
Toward a FAIR information culture in open government – Focuses on socio-technical research to improve government supply-side practices so data is accessible in FAIR ways.
Sources and evidence values of records in open government – Focuses on socio-technical research regarding demand-side open data practices and the authoritativeness/evidence value of records.
From Legal Text to Executable Decision Models: Evaluating Structured Representations for Legal Decision Model Generation Proceedings Article
In: Proceedings of the International Conference on Artificial Intelligence and Law (ICAIL), ACM, Singapore, 2026.
From Formal Transparency to Practical Interpretability: WOOLens for Open Government Data Miscellaneous
2026.
Linking References to Documents in Parliamentary Debates Proceedings Article
In: Proceedings of the 29th International Conference on Theory and Practice of Digital Libraries, Springer, Tampere, Finland, 2026.
Out of the Box: Zero-Shot Vision-Language Models for Redaction Detection and Page-Stream Segmentation Miscellaneous
2026.
Sensitivity-Aware Retrieval-Augmented Intent Clarification Miscellaneous
2026, (_eprint: 2603.06025).
Spoken Question Answering on Municipal Council Meetings Proceedings Article
In: Advances in Information Retrieval: 47th European Conference on Information Retrieval, ECIR 2025, pp. 41–46, Springer, Lucca, Italy, 2026.
WCAG Compliance of Open Government Documents Proceedings Article
In: New Trends in Theory and Practice of Digital Libraries, pp. 176–184, Springer Nature Switzerland, Cham, 2026, ISBN: 978-3-032-06136-2.
From Quotes to Concepts: Axial Coding of Political Debates with Ensemble LMs Miscellaneous
2026.
Beyond Disclosure: Evaluating Algorithmic Transparency in the Dutch Algorithm Register Bachelor Thesis
2025.
University of Amsterdam (UvA) is a major public research university in the Netherlands that provides higher education and conducts academic research across various disciplines, including humanities and informatics (such as the ILLC and IvI sub-institutes mentioned in the application).
National Oragnisation for Information Management (RvIHH) focuses on improving, professionalizing, and supporting government-wide information management and archiving practices.
National Organisation for Development, Digitalisation and Innovation (ODI) is a Dutch government service organization that supports public sector agencies with digital transformation, organizational development, and innovation initiatives.
Ministry of Interior and Kingdom Relations (BZK) is responsible for government administration, public sector organization, democratic governance, and constitutional matters.
