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Datasets:
SNTIQ-Team
/
amtsgraph

Modalities:
Tabular
Text
Formats:
json
Languages:
German
Size:
100K - 1M
Tags:
germany
legal
government
courts
public-administration
graph
Libraries:
Datasets
pandas
Polars
License:
Dataset card Data Studio Files
xet
 Community
1
amtsgraph / README.md
David Glushkov
Refresh 2026-07-06: add BAMF + federal authorities, AsylbLG noise cleanup + Bavaria ANKER caveat
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metadata 
license: other
license_name: sntiq-dual-by-audience
license_link: https://github.com/SNTIQ-Team/amtsgraph/blob/main/LICENSING.md
language:
  - de
pretty_name: Amtsgraph — German public-authority competence graph
tags:
  - germany
  - legal
  - government
  - courts
  - public-administration
  - graph
size_categories:
  - 100K<n<1M
configs:
  - config_name: authorities
    data_files: authorities.jsonl
  - config_name: court_chains
    data_files: court_chains.jsonl
  - config_name: competences
    data_files: competences.jsonl
  - config_name: edges
    data_files: edges.jsonl
  - config_name: places_courts
    data_files: places_courts.jsonl
  - config_name: municipalities
    data_files: municipalities.jsonl
  - config_name: matters
    data_files: matters.jsonl
  - config_name: caveats
    data_files: caveats.jsonl

Amtsgraph

The open, validated graph of German public authorities — who is competent, where, and for what.

Built 2026-07-06 from official registers (Orts- und Gerichtsverzeichnis, PVOG/FITKO, Bundesagentur für Arbeit, Destatis, BayernPortal, OpenPLZ, xRepository). Every build passes a validation gate (coverage, collision, contiguity, benchmark checks) before release; every record carries provenance (source, URL, fetch timestamp).

Files

File Rows Content
authorities.jsonl 19,746 all authorities with contacts, provenance, external IDs
court_chains.jsonl 338,873 instance chains per (plz, ortk, matter)
competences.jsonl 77,125 kind × area assignments (rank 0 = apply here)
edges.jsonl 8,394 parent / supervision / appeal / successor relations
places_courts.jsonl 14,057 official court-resolution place register
municipalities.jsonl 10,950 AGS/ARS spine with postal codes (M:N)
matters.jsonl 36 legal-matter taxonomy (14 core + special)
caveats.jsonl 5,372 warnings that must be surfaced with answers

Resolution logic

  1. Courts: look up places_courts by postal code (+ locality when one code spans several court districts), then court_chains by (plz, ortk, matter) — rows ordered by position are the full instance chain (role court) plus prosecution offices (role prosecution). Join authorities for contacts and filing addresses.
  2. Agencies: map the user's municipality to its ags via municipalities, then filter competences by kind and area (gemeinde = 8-digit AGS, kreis = 5-digit prefix, land = 2-digit). rank 0 = the office to apply at; rank 1 = supervisory body.
  3. Always join caveats for the scope you resolved — they flag genuine ambiguities and register gaps. For legal use, an honest warning beats a confident wrong answer.
  4. The organisational web (Bavaria): traverse edges with relation='parent' for department hierarchies, 'supervision' for oversight, 'appeal' for derived court appeal routes.

Null semantics

Empty fields are deliberate, not dirty data:

  • legal_form is only defined for Jobcenter (gE = joint federal-municipal institution, zkT = municipal provider); for every other kind it is null.
  • For courts, the full visiting address (street + postal code + city) lives in street as published by the justice register, and the separate postal-box address in postal_address; the plz/city columns are filled where sources provide them as discrete fields (agencies), null otherwise.
  • valid_to is null for active records; a timestamp marks retired ones (kept for traceability — e.g. offices replaced by a more precise department).
  • matter on edges is null for non-court relations (parent, supervision).
  • external_ids may be empty for organisational units that have no official register identity of their own.

Important notes

  • General information, not legal advice; statutory exceptions to competence rules exist that no dataset can capture.
  • Department-level depth covers Bavaria's 96 Kreisverwaltungsbehörden (pilot); other Länder resolve at authority level.
  • Underlying records originate from official public registers; their respective terms govern redistribution (see the source registry in the GitHub repository). Dual-licensed by audience: non-commercial / human-rights / research use under Apache-2.0 (code) + CC BY-NC-SA 4.0 (data); commercial, corporate and governmental use under the SNTIQ-CM License v1.0 (free written permission, non-harm covenant, attribution, reciprocity) — see LICENSING.md in the GitHub repository.

Citation 

@misc{amtsgraph2026,
  title   = {Amtsgraph: an open validated graph of German public
             authorities, court competences and organisational structure},
  author  = {Glushkov, David and {SNTIQ}},
  year    = {2026},
  url     = {https://github.com/SNTIQ-Team/amtsgraph}
}

Source code, pipeline and full documentation: https://github.com/SNTIQ-Team/amtsgraph