We extract DCAT-AP metadata, dataset distributions, publisher catalogues, and SPARQL endpoint results from data.europa.eu. Delivered as clean JSON, CSV, or Parquet to your warehouse.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Dataset Metadata objects from data.europa.eu. All fields typed and schema-versioned.
"dataset_id": "eurostat-nama_10_gdp", "title": "GDP and main components", "publisher_name": "Eurostat", "theme": "Economy and finance", "issued_date": "2015-10-14T05:00:00Z", "modified_date": "2023-11-02T23:00:00Z", "license": "CC BY 4.0", "keywords": "['national accounts', 'economic growth', 'GDP']"
| # | dataset_id | title | description | publisher_name | publisher_type | theme |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Distributions (Files) objects from data.europa.eu. All fields typed and schema-versioned.
"distribution_id": "dist-8f4a-4b2c", "dataset_id": "eurostat-nama_10_gdp", "format": "TSV", "media_type": "text/tab-separated-values", "download_url": "https://ec.europa.eu/eurostat/api/dissemination/sdmx/2.1/data/nama_10_gdp", "byte_size": 458021, "modified_date": "2023-11-02T23:00:00Z", "status": "Available"
| # | distribution_id | dataset_id | title | format | media_type | download_url |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Catalogues objects from data.europa.eu. All fields typed and schema-versioned.
"catalogue_id": "gov-data-fr", "title": "data.gouv.fr", "publisher": "Etalab", "dataset_count": 45210, "language": "fr", "spatial": "France", "modified_date": "2023-11-10T14:22:00Z"
| # | catalogue_id | title | description | publisher | homepage | spatial |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Publishers objects from data.europa.eu. All fields typed and schema-versioned.
"publisher_id": "pub-ec-jrc", "name": "Joint Research Centre", "type": "EU Institution", "country": "EU", "dataset_count": 3105, "website": "https://joint-research-centre.ec.europa.eu"
| # | publisher_id | name | type | country | website | |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for SPARQL Results objects from data.europa.eu. All fields typed and schema-versioned.
"query_id": "sq-77b1-99c0", "endpoint_url": "https://data.europa.eu/sparql", "subject": "http://data.europa.eu/88u/dataset/eurostat-nama_10_gdp", "predicate": "http://purl.org/dc/terms/title", "object": "GDP and main components", "language_tag": "en", "execution_time": "145ms"
| # | query_id | endpoint_url | subject | predicate | object | graph |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Data.europa.eu aggregates hundreds of national and institutional catalogues. We handle the DCAT-AP normalisation, broken link detection, and endpoint pagination so you receive clean, queryable records.
Parse deeply nested DCAT-AP metadata structures including datasets, distributions, catalogues, and data services across all namespaces.
Automatically verify and resolve download URLs for CSV, JSON, RDF, and XML distributions before delivering the metadata record.
Extract and map titles, descriptions, and keywords across 24 official EU languages into a unified, queryable schema.
Track dataset additions and modifications at the catalogue level, from Eurostat to national portals like data.gouv.fr.
Execute complex semantic queries against the portal's SPARQL endpoint with automated pagination and rate-limit handling.
Extract GeoJSON boundaries, NUTS classifications, and spatial coverage metadata for regional analysis pipelines.
Identify and map high-value Eurostat datasets, capturing SDMX-ML structures and TSV distribution endpoints.
Standardise varying open-data license strings into boolean flags for commercial reuse eligibility.
Monitor modification timestamps across 1.7M datasets to push only updated records to your warehouse.
Brief in. Clean data out.
Specify target catalogues, themes, publishers, or file formats. We configure the extraction schema.
We deploy Scrapy spiders and SPARQL wrappers to paginate through the portal's APIs and semantic endpoints.
Schema alignment, dead-link filtering, and language-tag normalisation ensure data consistency.
Clean JSON, CSV, or Parquet delivered to your S3 bucket or Snowflake instance on your required cadence.
Aggregating data from 27 member states creates massive schema inconsistencies. Here is how we build resilience into the pipeline.
Different member states implement DCAT-AP differently. We map custom extensions, missing mandatory fields, and varying date formats into a single, strict JSON schema before delivery.
Public data portals suffer from link rot. Our pipeline issues HEAD requests to distribution URLs, flagging 404s and resolving redirects so your downstream processes do not fail on dead links.
The public SPARQL endpoint enforces strict query timeouts and rate limits. We chunk large semantic queries, implement exponential backoff, and rotate IPs to extract massive graphs without triggering bans.
Fetching 1.7M dataset records requires deep pagination. We parallelise requests across catalogue partitions and use cursor-based traversal to ensure zero data loss during full syncs.
Datasets often contain metadata in multiple languages. We extract all available language tags and structure them in nested JSON, allowing you to filter for your preferred locale easily.
Financial institutions ingest Eurostat and national economic datasets to build predictive models for inflation and GDP growth.
Think tanks and NGOs track environmental, social, and governance datasets across member states to measure policy impact.
Enterprise sales teams monitor Tenders Electronic Daily (TED) metadata to identify public sector contract opportunities.
Logistics companies extract NUTS regional boundaries and transport infrastructure datasets to optimise supply chain routing.
Climate tech startups ingest emissions and energy consumption data from the European Environment Agency to train assessment models.
Universities compile massive historical datasets on demographics and public health to support longitudinal studies.
"Data.europa.eu aggregates the continent's public data, but extracting consistent, queryable records across 180 disjointed national catalogues requires serious infrastructure."
Public data portals are notorious for inconsistent metadata, broken distribution links, and varying DCAT-AP implementations. DataFlirt standardises this chaos, handling rate limits, schema alignment, and multi-lingual normalisation so your analysts can query clean EU data instantly without writing a single parser.
Everything supported by our data.europa.eu scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
We interact directly with the portal's REST APIs and SPARQL endpoints, managing pagination cursors and connection pools to extract metadata efficiently.
Custom Python 3.12 processors align disparate DCAT-AP namespaces, fix malformed dates, and structure multi-lingual fields into strict JSON schemas.
Airflow schedules delta syncs across 180+ catalogues. ECS containers handle the extraction load, with state and execution logs managed in PostgreSQL.
Data delivered to where your team already works — no new tooling required.
About data.europa.eu scraping, legality, and pipeline operations.
Ask us directly →Yes. Data.europa.eu is an open data portal designed for public access and reuse. The metadata and datasets are published under open licenses (such as CC BY 4.0 or public domain). We extract this public information strictly adhering to API rate limits and terms of service.
We primarily extract the DCAT-AP metadata and distribution links. However, we can configure pipelines to automatically download, parse, and deliver specific file formats (like CSV or JSON) from those distribution links if required by your use case.
Our pipelines issue HEAD requests to validate distribution URLs. We flag broken links (404s), resolve redirects, and provide a status field in the output so your systems can ignore dead distributions automatically.
Yes. We can scope the pipeline to target specific catalogues (e.g., data.gouv.fr), specific Eurovoc themes (e.g., Economy and finance), or specific publishers (e.g., Eurostat).
We configure pipelines based on your needs. For high-velocity datasets like procurement notices, we can run hourly syncs. For general catalogue updates, daily or weekly delta runs are standard.
We extract all available language variants for titles and descriptions. The output JSON structures these with ISO language tags, allowing you to select your preferred language or process all translations.
Our normalisation engine acts as a buffer. We monitor for schema drift across the 180+ source catalogues. If a publisher alters their DCAT-AP implementation, we update our mapping logic to ensure your downstream schema remains stable.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a full sync of Eurostat indicators or continuous monitoring of member state procurement portals, we build and manage the infrastructure. Tell us your requirements.
