# Crossref DOI Metadata Search (`scrupulous_waterbird_m4w/crossref-doi-metadata`) Actor Search Crossref scholarly works or resolve DOI metadata into clean structured records, including titles, authors, publishers, dates, types, citations, licenses, and canonical URLs. Uses the public Crossref API with no API key required. - **URL**: https://apify.com/scrupulous\_waterbird\_m4w/crossref-doi-metadata.md - **Developed by:** [Mori](https://apify.com/scrupulous_waterbird_m4w) (community) - **Categories:** Education, Developer tools - **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Crossref DOI Metadata Search Search Crossref scholarly works or resolve DOI metadata into clean structured records — titles, authors, publishers, dates, types, citation/reference counts, licenses, ISSNs, ISBNs, subjects, and canonical DOI resolver URLs. Two modes in one actor: - **Search mode** — supply a free-text `query` and get back ranked works. - **DOI mode** — supply a list of `dois` and get back one structured record per DOI. Both modes use Crossref's public REST API (`https://api.crossref.org/`). No API key, no proxy, no captcha, no browser. ### What it does - Hits `/works?query=...` for free-text search and `/works/{doi}` for direct DOI resolution. - Projects each work into a stable schema with `doi`, `title`, `authors[]`, `publisher`, `containerTitle`, `publishedDate`, `issuedDate`, `referenceCount`, `citationCount`, `isReferencedByCount`, `subjects[]`, `licenses[]`, `language`, `issn[]`, `isbn[]`, `url`, `resourceUrl`, `sourceQuery`, `fetchedAt`. - Strips `` and other XML tags from abstracts; resolves ORCID URLs to bare ORCIDs. - Deduplicates search results by lowercased DOI. - DOI mode failures push an `{doi, sourceQuery, fetchedAt, error}` warning row instead of crashing the whole run. - Polite-pool User-Agent + ~3 req/sec throttle between DOI calls. ### Input | Field | Required | Default | Description | |---|---|---|---| | `query` | one of | — | Free-text work search (search mode) | | `dois` | one of | — | DOIs to resolve (DOI mode); array of strings | | `maxItems` | no | `50` | Max results from a search (1–500) | | `start` | no | `0` | Pagination offset (0–100000) | | `fromPublishedDate` | no | — | `YYYY[-MM[-DD]]` lower bound (search mode) | | `untilPublishedDate` | no | — | `YYYY[-MM[-DD]]` upper bound (search mode) | | `types` | no | — | Crossref work types (e.g. `journal-article`, `book-chapter`) | | `sort` | no | `relevance` | `relevance` \| `published` \| `is-referenced-by-count` | At least one of `query` or `dois` must be non-empty. Mode is picked by which is supplied (search wins if both are given). ### Output One dataset record per work. Search-mode example: ```json { "doi": "10.1093/oso/9780198828044.003.0003", "title": "Machine learning with sklearn", "authors": [ { "given": "Thomas P.", "family": "Trappenberg", "orcid": null, "affiliation": [] } ], "publisher": "Oxford University Press", "containerTitle": "Fundamentals of Machine Learning", "type": "book-chapter", "publishedDate": "2019-11-28", "issuedDate": "2019-11-28", "referenceCount": 0, "citationCount": 19, "isReferencedByCount": 19, "language": "en", "issn": [], "isbn": ["9780198828044", "9780191883873"], "url": "https://doi.org/10.1093/oso/9780198828044.003.0003", "resourceUrl": "https://academic.oup.com/book/36775/chapter/321905277", "sourceQuery": "machine learning", "fetchedAt": "2026-07-16T16:30:00.000Z" } ```` DOI-mode records look identical except `sourceQuery` is the DOI itself. ### Limitations - Pure public REST wrapper — does not scrape paywalled publisher pages. - `reference-count` and `references-count` may both appear in Crossref records; this actor prefers `references-count` (canonical newer field) and falls back to `reference-count` only if missing. - `subject` is sometimes `[]` for works without FACET data — emitted as empty array, not null. - `abstract` HTML/JATS tags are stripped; tag content remains as plain text with entity decoding for `&`, `<`, `>`, `"`, `'`, ` `. ### Pricing Free tier: 100 runs/month on the public Apify free plan. Public Store tier not yet enabled for this actor. ### Changelog - 0.1.0 — initial release. # Actor input Schema ## `query` (type: `string`): Free-text work search across Crossref's metadata index. Leave empty when supplying DOIs. ## `dois` (type: `array`): List of DOIs to resolve directly via the Crossref /works/{doi} endpoint. Leave empty when supplying a search query. ## `maxItems` (type: `integer`): Maximum number of works to emit from a search. Crossref caps rows at 500. ## `start` (type: `integer`): Pagination offset (0-indexed) for search mode. Default 0. ## `fromPublishedDate` (type: `string`): Inclusive lower bound on published date for search mode (Crossref filter syntax: from-pub-date). ## `untilPublishedDate` (type: `string`): Inclusive upper bound on published date for search mode (Crossref filter syntax: until-pub-date). ## `types` (type: `array`): Restrict to specific Crossref work types (e.g. journal-article, book-chapter, proceedings-article). Applied as a comma-joined `filter=type:...` clause. ## `sort` (type: `string`): Sort order for search results. ## Actor input object example ```json { "maxItems": 50, "start": 0, "sort": "relevance" } ``` # Actor output Schema ## `doi` (type: `string`): No description ## `title` (type: `string`): No description ## `subtitle` (type: `string`): No description ## `abstract` (type: `string`): No description ## `authors` (type: `string`): No description ## `publisher` (type: `string`): No description ## `containerTitle` (type: `string`): No description ## `type` (type: `string`): No description ## `publishedDate` (type: `string`): No description ## `issuedDate` (type: `string`): No description ## `createdDate` (type: `string`): No description ## `updatedDate` (type: `string`): No description ## `referenceCount` (type: `string`): No description ## `citationCount` (type: `string`): No description ## `isReferencedByCount` (type: `string`): No description ## `subjects` (type: `string`): No description ## `licenses` (type: `string`): No description ## `language` (type: `string`): No description ## `issn` (type: `string`): No description ## `isbn` (type: `string`): No description ## `url` (type: `string`): No description ## `resourceUrl` (type: `string`): No description ## `sourceQuery` (type: `string`): No description ## `fetchedAt` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("scrupulous_waterbird_m4w/crossref-doi-metadata").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("scrupulous_waterbird_m4w/crossref-doi-metadata").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call scrupulous_waterbird_m4w/crossref-doi-metadata --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrupulous_waterbird_m4w/crossref-doi-metadata", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Crossref DOI Metadata Search", "description": "Search Crossref scholarly works or resolve DOI metadata into clean structured records, including titles, authors, publishers, dates, types, citations, licenses, and canonical URLs. Uses the public Crossref API with no API key required.", "version": "0.0", "x-build-id": "3hECgTVqNGA5tOtPH" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrupulous_waterbird_m4w~crossref-doi-metadata/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrupulous_waterbird_m4w-crossref-doi-metadata", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrupulous_waterbird_m4w~crossref-doi-metadata/runs": { "post": { "operationId": "runs-sync-scrupulous_waterbird_m4w-crossref-doi-metadata", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrupulous_waterbird_m4w~crossref-doi-metadata/run-sync": { "post": { "operationId": "run-sync-scrupulous_waterbird_m4w-crossref-doi-metadata", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "query": { "title": "Search query", "type": "string", "description": "Free-text work search across Crossref's metadata index. Leave empty when supplying DOIs." }, "dois": { "title": "DOIs to resolve", "type": "array", "description": "List of DOIs to resolve directly via the Crossref /works/{doi} endpoint. Leave empty when supplying a search query.", "items": { "type": "string" } }, "maxItems": { "title": "Max results", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of works to emit from a search. Crossref caps rows at 500.", "default": 50 }, "start": { "title": "Offset", "minimum": 0, "maximum": 100000, "type": "integer", "description": "Pagination offset (0-indexed) for search mode. Default 0.", "default": 0 }, "fromPublishedDate": { "title": "From published date (YYYY[-MM[-DD]])", "type": "string", "description": "Inclusive lower bound on published date for search mode (Crossref filter syntax: from-pub-date)." }, "untilPublishedDate": { "title": "Until published date (YYYY[-MM[-DD]])", "type": "string", "description": "Inclusive upper bound on published date for search mode (Crossref filter syntax: until-pub-date)." }, "types": { "title": "Work types filter", "type": "array", "description": "Restrict to specific Crossref work types (e.g. journal-article, book-chapter, proceedings-article). Applied as a comma-joined `filter=type:...` clause.", "items": { "type": "string" } }, "sort": { "title": "Sort order", "enum": [ "relevance", "published", "is-referenced-by-count" ], "type": "string", "description": "Sort order for search results.", "default": "relevance" } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```