EU recitals as open data
Recitals explain why an article reads the way it does, and they are cited daily in questions of interpretation. Here they sit as an open surface: every recital has a number, a heading, an address, a hash and a reading date, enough to cite correctly and to notice when something changed.
NovaCopilot · ExploreWorld Legal
European and Nordic law as verifiable data, with source, reading date and checksum on every row.
- Publisher
- NovaCopilot, ExploreWorld Legal
- Corpus version
- legal-2026-10-07
- Read at
- 2026-08-31
- Freshness
- 87/100
What the surface gives out
- The act the recital belongs to, with its CELEX identifier.
- The recital number and heading, and the canonical address.
- Hash and reading date per row, so a copy can be checked against the original.
- A freshness score, so a reader sees how recently the row was re-read.
How to fetch it
- The address is /api/public/v1/open/eu/recitals and answers without a key.
- Responses carry ETag and Last-Modified; unchanged content returns 304 instead of the whole file.
- A next-check date travels with the response, so a fetcher knows when returning is worthwhile.
- Terms are the same as the rest of the open layer: use, cite, index, cache, do not resell the dataset as such.
The boundary
- The full body text of the recitals is not part of the open surface.
- Reasoning, bulk extraction and agent surfaces are priced as before.
- Metadata, citation string, hash and freshness are free and stay free.
What the usage shows
- NovaCopilot is used by professional lawyers and compliance teams in 17 countries.
- The agent API is used in product evaluations by international teams.
- AI Act articles are read in sequence, a clear sign of regulatory use.
Professional roles on this surface
Every row is its own node with source, reading date, hash and the same answer as data.
Workflows on this surface
Every row is its own node with source, reading date, hash and the same answer as data.
The articles the surface touches
Every row is its own node with source, reading date, hash and the same answer as data.
- GDPR, 5: Principles relating to processing of personal data
- GDPR, 7: Conditions for consent
- GDPR, 6: Lawfulness of processing
- GDPR, 13: Information to be provided where personal data are collected from the data subject
- GDPR, 22: Automated individual decision-making, including profiling
- GDPR, 32: Security of processing
- GDPR, 33: Notification of a personal data breach to the supervisory authority
- GDPR, 35: Data protection impact assessment
- GDPR, 46: Transfers subject to appropriate safeguards
- GDPR, 83: General conditions for imposing administrative fines
- AI Act, 6: Classification rules for high-risk AI systems
- AI Act, 5: Prohibited AI practices
- AI Act, 9: Risk management system
- AI Act, 17: Quality management system
- AI Act, 43: Conformity assessment
- AI Act, 49: Registration
- AI Act, 50: Transparency obligations for providers and deployers of certain AI systems
- AI Act, 71: EU database for high-risk AI systems listed in Annex III
- AI Act, 99: Penalties
- DORA, 17: ICT-related incident management process
- DORA, 28: General principles
The NovaCopilot models
The decision model
In: A role, a legal act and the situation in plain words.
Out: The obligations that reach the role, the article behind them and what remains.
When: When the question is whether a requirement applies to you, and why.
The difference model
In: A checksum already used and the date of the last reading.
Out: What changed since then: checksum, reading date, passed deadline and rows to revisit.
When: When earlier work is reused and has to be checked first.
The obligation model
In: A legal act or an article, with or without a role filter.
Out: The obligation in the register's wording, the role it reaches, canonical address and reading date.
When: When the answer has to be citable article by article.
Example for an agent
curl -s "https://legal.exploreworldai.com/novacopilot/eu-skal?format=agent"- canonical, the address to cite
- node_hash, the checksum for the next comparison
- corpus_version, the corpus version that answered
- freshness.read_at, the reading date of the row
- freshness.next_check, when a new check is reasonable
- citation.string, the finished citation
- agent.receipt, the receipt of the call, without a key
Metadata
- Canonical address
- https://legal.exploreworldai.com/novacopilot/eu-skal
- Layer
- index
- Read at
- 2026-08-31
- Freshness
- 87/100
- Checksum
- 7c0317682e1d87cd
- Corpus version
- legal-2026-10-07
- Next check
- -
- License
- https://legal.exploreworldai.com/revision
How to cite this page
NovaCopilot (ExploreWorld Legal, Valkiv Ventures AB), https://legal.exploreworldai.com/novacopilot/eu-skal, read 2026-08-31, checksum 7c0317682e1d87cd, corpus version legal-2026-10-07, license https://legal.exploreworldai.com/revision
- Owner
- Valkiv Ventures AB
- License
- https://legal.exploreworldai.com/revision
- Checksum
- 7c0317682e1d87cd
- Fingerprint
- ewai:eu:89e122
- Terms
- Use, cite, index and cache. The register as such is not resold.
Source registers
The same material as registers, with read date and source on every row.
French edition
The same node in French, with the same read date, checksum and citation.
FAQ
- May we use the surface commercially?
- Yes. Use, cite, index and cache freely. The only thing not permitted is reselling the dataset as such.
- How do we know a row is unchanged?
- Compare the hash. The same hash means the same row; a change also shows in the change journal with a date.
- How often are recitals updated?
- Every row carries its own reading date and freshness score, and the response states when the next check is reasonable.
Next step
Three ways to put the register to work in your own practice.
Start with your task
Litigation
Find support in a judgment
Search guiding decisions, see what became final and follow changes in the law.
In-house, deals
Map the rules in a transaction
Move from theme to act and on to the article that carries the duty.
Compliance
Assess the risk in a process
Risk scoring per legal area, with the sources behind every score.