Compare UN Security Council Sanctions Regimes

Analyze record counts and update patterns across UN list types without assuming uniform measures. The UN Sanctions List Scraper turns each public UN consolidated-list record into a bounded Apify dataset row and preserves a direct source URL for verification.

Start with a reviewable sample

{"recordType":"Entity","queries":[],"regimes":[],"maxResults":500}

Begin with ten to one hundred records, not a full archive. Inspect identifier stability, date formats, nulls, arrays, free-text fields, and source links. Group by UN list type, but read the responsible committee page before interpreting what a listing means. Once the sample matches the intended workflow, raise the result limit deliberately and save the input as a named Apify Task.

Design the dataset around source truth

Keep data ID, permanent reference number, record type, primary and original-script names, aliases, regime, listing date, update dates, nationalities, addresses, comments, and source URL together in the raw landing table. Do not replace missing values with zero, invent status labels, or silently collapse aliases. Use the publisher's stable identifier as the upsert key where one exists; otherwise combine the canonical source URL and observed identifier. Add a downstream collection timestamp so analysts can distinguish a revised record from a newly published record.

A useful pipeline has three layers. The raw layer stores the Actor output without lossy transformations. The review layer adds normalized dates, currencies, or matching candidates while preserving original fields. The application layer contains only decisions that have passed the organization's validation rules. This separation makes source changes auditable and prevents a convenient spreadsheet formula from becoming an undocumented business rule.

Schedule changes without creating alert noise

Run the Task on a cadence appropriate to how often United Nations Security Council changes. Compare stable keys and material fields rather than array order or page position. Send alerts only for additions, removals, deadline changes, status changes, or other changes relevant to the workflow. Store the previous snapshot in a table or object store and make the diff reproducible.

For operational use, log the Actor run ID, dataset ID, input, source URL, and collection time. Use retries for transient network failures, but fail visibly when the publisher returns no records for a query that normally has coverage. Silent empty datasets are more dangerous than explicit failures because they can look like a legitimate all-clear.

Validate before acting

The consolidated list spans distinct Security Council regimes with different measures and criteria. A name match is not identity resolution. Verify the permanent reference, identifiers, committee context, and current official record with human review. The Actor is a collection tool, not a substitute for due diligence, legal interpretation, financial analysis, or publisher methodology. Reviewers should open the source URL, confirm that the record is current, and document the evidence used for any material conclusion.

This workflow is designed for sanctions researchers, compliance teams, policy analysts, and auditors. It is an independent integration and is not affiliated with or endorsed by United Nations Security Council.

Regime counts are descriptive, not directly comparable

UN list types correspond to different Security Council committees, mandates, histories, and listing criteria. Count individuals and entities separately by regime, then calculate additions and amendments over a defined window. A larger list does not imply a more severe threat, better enforcement, or broader measures.

Permanent reference prefixes help validate grouping, but use the explicit UN_LIST_TYPE field as published. Track missing aliases, addresses, and update dates as data-completeness measures. Regimes with older records may have different documentation practices than newer regimes, which affects apparent richness.

When publishing a comparison, link each group to its committee materials and explain that the consolidated list facilitates implementation without making regimes uniform. Keep narrative comments out of simplistic sentiment or risk scores; they were written for identification and committee context, not statistical comparability.

Why use an Apify Task

A Task makes the exact input repeatable across schedules, webhooks, the API, Make, Zapier, n8n, and MCP clients. Keep one Task per business question instead of one enormous catch-all export. Small Tasks are easier to test, cheaper to rerun, and clearer when a source field or filter changes. The Thirdwatch Actor on Apify provides JSON, CSV, Excel, RSS, and API access to the resulting dataset.