Towards Translating Natural Language Normative Text into a Digital Twin of Administrative Law

Automating public-sector decision-making promises efficiency gains in administration. This short paper proposes a research agenda for translating natural-language normative text into a Digital Twin of Administrative Law (DTAL), which we envision as a layered, executable representation of statutes that preserves traceability to the authoritative legal text while enabling accountable automation of decision-making in the public sector. To obtain a DTAL from normative text, a stepwise translation pipeline must be followed, which we demonstrated on the Upper Austrian Tourism Contribution Levy Act. The resulting DTAL yields deterministic and explainable outcomes. In this short paper, we outline open questions on standardizing legal ontologies, integrating LLMs as assistant tools, and embedding DTALs into public-sector engineering practices to realize transparent auditable automation of decision-making aligned with the rule of law.

Keywords: Legal ontologies, law as code, digital twin of legislation, automated decision-making, administrative law