Build a reference collection
Organise article identities, sections and source links for a searchable knowledge base or research workflow with clear provenance.
All use casesWikipedia
OPEN KNOWLEDGE / SOURCE-LINKED DATA
Wikipedia
page data.
Knowledge you can use.
Sources you can trace.
Turn public articles into structured records, with page identity, infobox fields and references connected to their source revision.
FROM ENCYCLOPEDIA TO WORKING DATASET
Useful knowledge.
Without losing the source.
Build around selected topics and language editions. Keep article content, structured fields and your own analysis distinct.
Connect related records
Use page IDs and available Wikidata identifiers to join topic records. Keep language-specific coverage and field mappings explicit.
Follow meaningful changes
Compare observed revisions and selected fields over time. Separate an article edit from the date your collection actually ran.
A REAL, SOURCE-LINKED SNAPSHOT
One article.
Three useful views.
Selected data from the English Wikipedia article on Mount Everest. Captured on 10 October 2026 through the Wikimedia MediaWiki API, without AI extraction.
Identify the page and the version.
A title can change. Preserve the page ID, language and revision alongside the source URL so records remain traceable.
- page_id / title / language
- Article identity within its language edition.
- revision_id / revision_at
- The observed source revision, not the collection time.
- wikidata_id / source_url
- Entity linkage and the original Wikipedia article.
- section_count / observed_at
- Parsed section coverage and collection timestamp.
Collected snapshot / 10 October 2026
{
"record_type": "article",
"source": "Wikipedia",
"page_id": 42179,
"revision_id": 1376942985,
"source_url": "https://en.wikipedia.org/wiki/Mount_Everest",
"observed_at": "2026-10-10T13:58:14.336Z",
"title": "Mount Everest",
"language": "en",
"revision_at": "2026-09-27T02:29:28Z",
"revision_url": "https://en.wikipedia.org/w/index.php?oldid=1376942985",
"wikidata_id": "Q513",
"section_count": 65,
"attribution": {
"source": "Wikipedia contributors / Wikimedia Foundation",
"article_url": "https://en.wikipedia.org/wiki/Mount_Everest",
"revision_url": "https://en.wikipedia.org/w/index.php?oldid=1376942985",
"license": "CC BY-SA 4.0",
"license_url": "https://creativecommons.org/licenses/by-sa/4.0/",
"changes": "Selected metadata and infobox/reference fields; HTML removed and whitespace normalized. No full article or images included."
}
}Selected source fields. Not a live article check.
Collected from the Wikimedia MediaWiki Action API. This is a normalized snapshot, not its native response or a built-in ScrapingBuddy endpoint.
Source: Wikipedia contributors, via Wikimedia. Mount Everest / Source revision / CC BY-SA 4.0
Selected metadata and infobox/reference fields; HTML removed and whitespace normalized. No full article or images included.
A limited validation sample, not a live feed, complete article or independent fact check. A managed delivery schema is agreed for your project; these fields are not a built-in response from the general Scraping API.
THE CONTEXT BELONGS IN THE RECORD
Keep the detail
that changes the meaning.
Clean JSON is only useful when you can tell which article it came from, what its values mean and which version was observed.
Language is part of the key
Titles and page IDs belong to a wiki edition. A linked topic in another language is not automatically the same article.
A label is not a universal field
Keep the original infobox label, value, units and qualifiers before turning them into a common reporting schema.
A citation is a source link
Reference counts include different kinds of notes. A collected link does not mean its contents or the claim have been verified.
USE THE SIMPLEST SUITABLE ROUTE
Start structured.
Scale with a plan.
Our sample needed neither browser rendering nor AI. Match the collection method to the fields and volume before adding more processing.
- 01 / IDENTIFY
Resolve the article
Confirm the language, canonical URL, page identity and redirects. Keep missing and disambiguation pages out of a silently merged result.
- 02 / EXTRACT
Take the fields you need
Use Wikimedia metadata and revision-aware parsed content. Extract tables and reference links deterministically; add AI only for a separate analysis requirement.
- 03 / MAINTAIN
Preserve provenance
Track revision and observation times, retain attribution and respect rate signals. Cache unchanged data and report incomplete runs.
API-first collection
Direct MediaWiki calls supplied this sample without a paid scraper or AI call. A separate raw-HTML provider request also returned the article. Native structured access is the leaner starting point for these fields.
MediaWiki Action APIDumps or enterprise access
For large offline datasets, evaluate Wikimedia dumps. For high-volume commercial access and delivery requirements, review Wikimedia Enterprise. Freshness, engineering and operating costs still matter.
Wikimedia high-volume guidanceWikimedia is the source and API provider. Follow its usage guidelines and reuse terms. A successful test is not an unlimited-access or availability guarantee. Images require their own licence review.
YOUR WORKFLOW, YOUR LEVEL OF SUPPORT
Collect the page.
Or commission the dataset.
A page response and a maintained, revision-aware data collection solve different needs. Choose who should own the parsing and upkeep.
Scraping API
Collect supported public page content and handle your own extraction, source mapping and result validation.
- Content-only mode without AI processing
- Your URLs and downstream schema
- No CAPTCHA or login bypass
Managed Wikipedia data
Build an agreed dataset from Wikimedia sources with field mapping, provenance, refresh rules and delivery checks.
- Defined topics, languages and records
- Infobox mapping and revision-aware snapshots
- Attribution and agreed refresh/delivery format
BEFORE YOU BUILD ON THE DATA
Versions, structure
and reuse.
Should I use Wikipedia HTML, the API or a dump?
Use the Wikimedia MediaWiki API for selected page metadata and revision-aware content. HTML parsing is useful for rendered infoboxes and tables; our limited raw-HTML provider test also succeeded. For broad offline collections, evaluate Wikimedia dumps instead of making one page request per record. High-volume commercial delivery may suit Wikimedia Enterprise. Choose against the fields, freshness and operating requirements, not a promise that one route is always cheapest.
Can every infobox use the same JSON schema?
No. Templates, labels and units differ across topics and language editions, and some pages have no infobox. Keep source labels and values first, then apply an explicit field mapping. Preserve multiple values, units and qualifiers; an absent value stays missing instead of becoming zero or an AI guess. Nested tables need separate handling.
Does a revision ID guarantee an identical rendered page forever?
It identifies the article revision, but rendered output can also depend on templates, modules and other transcluded resources. Record the language, article ID, revision ID and observation time, and retain an appropriate snapshot for reproducibility. Our sample ties its metadata and parsed content to the same article revision; it is not a permanent freeze of every dependency.
Are different language editions exact translations?
No. Editions can differ in coverage, structure, facts and update timing. Keep the language and page ID together. Wikidata identifiers can help link corresponding topics, but a shared entity ID does not make two articles equivalent or verify their claims. Translation and normalization should remain separate from source content.
Do collected citations mean the underlying claims were verified?
No. This sample extracts citation links and identifiers from the article; it does not fetch the linked sites. Footnotes can be explanatory notes without a URL, and a reference may be unavailable or outdated. Verifying a claim or collecting an external source is a separate scope with its own access and licensing checks.
How should recurring collections handle limits and changes?
Use identifiable clients, bounded requests, caching and revision checks. Follow API continuation tokens when more results exist, and respect throttling, Retry-After and maxlag responses. Record partial runs and unavailable pages explicitly. Repeated retrieval of unchanged large pages wastes bandwidth and does not improve freshness.
What attribution and licensing belongs with the delivery?
Preserve source links, applicable licence information and a description of modifications. Wikipedia text is generally available under CC BY-SA, subject to page-specific notices and the relevant terms. Images and other media can have different licences. Our sample credits Wikipedia contributors, links its revision and CC BY-SA 4.0, and identifies the field selection and formatting changes. Wikimedia remains the API provider; we do not resell or guarantee its service.
START WITH THE RECORDS YOU NEED
What knowledge
should your dataset hold?
Share a few example articles and the fields you want. We can scope the collection method, sample validation and delivery before quoting the work.
- Topics, article URLs and language editions
- Required fields and reference handling
- Volume, refresh needs and output format
Projects are accepted individually, subject to feasibility and available capacity. An enquiry does not reserve a solution or confirm delivery. Pricing and terms are agreed directly with our team.
This sends a project enquiry. It does not run a collection or create a paid task.
ScrapingBuddy is independent of Wikipedia and the Wikimedia Foundation. The hero is an illustrative reference-book scene, not a Wikipedia interface. Source content remains subject to its applicable licences; our work is collection engineering and data delivery, not a resale of Wikimedia API access.