Industrial Gases · Publications Office of the European Union

data.europa.eu — EU open data portal

Datadory delivers data europa eu eu open data portal industrial gases data: 28 exact-match records drawn from a European catalogue of roughly 1.9 million harvested datasets spanning EU institutions and member-state portals - inventory reports, air-emissions tables, registry extracts with multilingual titles and per-record declared rhythms - delivered daily, weekly, or hourly.

API, files, or your warehouse. Daily, weekly, or hourly.

Where it covers
EU member states, EFTA countries, and EU institutions and agencies - whatever the harvested national and regional portals publish, with Austria, the United Kingdom, Spain and the Netherlands all present in the verified slice
How far back
Governed by each underlying dataset: many records are one-off publications declaring no maintenance rhythm, while others run long historical series - Dutch stationary-source air-emissions verified in-sample across 1990-2021
How fine
One metadata record per dataset; the grain beneath varies from national statistical tables to facility-level inventories and report documents

What is data.europa.eu — EU open data portal?

Europe publishes its public data through dozens of national portals and a stack of EU-institution catalogues, and somebody had the good sense to index all of them in one place. That place is data.europa.eu, operated by the Publications Office of the European Union: a DCAT-AP-harmonised shelf of roughly 1.9 million dataset records harvested from EU bodies - Eurostat and the European Environment Agency among them - and from national and regional portals such as opendataportal.at, data.gov.uk, datos.gob.es and data.overheid.nl.

Queried for this industry, the haystack compresses fast: an exact-phrase search for “industrial gases” returned 28 records at verification, while looser unquoted matching fanned out to roughly 54,000. What surfaces is not gas statistics in the neat time-series sense - it is the paper trail around the sector: national inventory reports, air-emissions tables, industrial-registry extracts, classification indices, each carrying multilingual titles, distribution formats and the publishing portal's own identifiers.

One caveat shapes everything else on this page: this is a discovery layer. Every record describes a dataset that still lives on the portal that published it. Get a sample of this dataset and Datadory hands you the resolved industrial-gases slice - records with their fields populated - instead of a list of places to look.

What does a sample of the industrial-gases slice look like?

Four of the 28 exact matches at verification, shown flat exactly as the catalogue describes them:

# 4 of 28 exact matches for the phrase “industrial gases”
title   : Austria’s National Inventory Report 2008
catalog : opendataportal.at
country : Austria
formats : PDF

title   : UKCCSRC Call 2 project poster: UK Demonstration of Enhanced Calcium Looping
catalog : data.gov.uk
country : United Kingdom

title   : National classes indices. IPRX-M (Identificador API: 67164)
catalog : datos.gob.es
country : Spain
formats : HTML, CSV, JSON, Excel XLSX

title   : Emissies naar lucht op Nederlands grondgebied; stationaire bronnen, 1990-2021
catalog : Dataportaal van de Nederlandse overheid
country : Netherlands

Read them as four different species of evidence. Row one is Austria's national inventory report - a greenhouse-gas inventory document published as a PDF, the kind of official paperwork that anchors a regulatory filing. Row two is a UK carbon-capture research poster, proof that the phrase reaches adjacent technology programmes, not only heavy industry. Row three is the sleeper: a Spanish national classification index shipping in four formats at once, which makes it the rare record here that drops straight into a parser. Row four is the analytical prize - the Netherlands' stationary-source air-emissions series running 1990 through 2021, three decades of facility-side emissions context for exactly the energy-intensive manufacturing that defines this industry's customer base.

Four countries, four portals, one query. That spread is the whole argument for treating this catalogue as the starting point rather than any single national portal.

What fields does the dataset include?

Eight documented fields carry every matched record, and they split into three jobs. result.count and country do the slicing - how big is the hit set, and which markets does it span. title, description and catalog do the identification, with the multilingual maps doing quiet work: a record titled only in Dutch still answers an English query, because the language key rides beside the text rather than inside it. And format.label, accrual_periodicity and is_hvd do the triage - which records are machine-readable, which are maintained, and which the EU itself designates as high-value.

Definitions below were checked against live responses during the August 2026 research pass, so the table describes what arrives rather than what a brochure promises. Two further elements ride on each distribution - the re-use terms the publisher attaches and the resolution pointer to the record's home portal - and both fold under additional fields on request so the core schema stays honest about what ships first.

How wide is the coverage across geography, time and granularity?

Geography - EU member states, EFTA countries, and EU institutions and agencies, in whatever shape the harvested portals publish. The verified industrial-gases slice alone spans Austria, the United Kingdom, Spain and the Netherlands. The honest framing: coverage is broad but not uniform - a large member state with a strong portal contributes differently from a small one with a sparse catalogue, and the record count tells you which is which.

Temporal - governed entirely by the underlying datasets, and the spread is wide. Many harvested records declare a one-off publication with no maintenance rhythm at all, while others run long historical series; the Dutch air-emissions table verified in this slice spans 1990-2021, and other holdings reach similarly deep. Currency is a per-record property you read off accrual_periodicity rather than something to assume portal-wide.

Granularity - one metadata record per dataset. Beneath that, grain varies from national statistical tables down to facility-level inventories and report documents. Treat the record as the address and the underlying dataset as the building.

How is the data delivered?

API, files, or your warehouse. Daily, weekly, or hourly.

You pick the channel and the cadence; resolution, cleaning and schema stability are our problem. Each matched record ships with its fields populated - titles, contributing catalogue, country, formats, declared rhythm and designation flags - normalised across however many portals contributed it. Bulk pulls land as files, continuous consumption runs through the API, and warehouse-native loads write straight into your own storage. A sample goes out first, cut to the countries and record types you actually need.

Who uses this data, and for what?

  • European regulatory-landscape mapping - national inventory reports and emissions tables surface country by country, giving market-entry teams the paperwork trail around gas-consuming industry before they commit capital.
  • Emissions baselining - stationary-source air-emissions series such as the Dutch 1990-2021 table put decades of facility-side environmental context behind any industrial-gases demand model.
  • Country screening and territory ranking - the country field splits one pan-European query into per-market reads, collapsing twenty-seven candidate markets into a ranked shortlist.
  • High-value dataset monitoring - the is_hvd flag separates records the EU designates as high-value from the long tail, a one-column importance filter most users never think to apply.
  • Adjacent-technology tracking - carbon-capture and industrial-decarbonisation programme records surface under the same queries, an early-read on where gas demand may erode or migrate.
  • Citation-grade sourcing - every record names its publishing portal and catalogue, so figures survive due diligence with provenance attached.

Which personas get the most value?

Market researchers and consultants sweep European public holdings once instead of learning each member state's portal taxonomy; see market researchers use cases. Competitive intelligence and product teams watch registry extracts and inventory publications across markets for signs of where gas-consuming capacity is being documented and permitted; see competitive intel product teams use cases. Data scientists and ML engineers mine emissions and inventory tables as exogenous features, with format labels revealing which records are parseable before any pipeline work; see data scientists use cases. Developers and data-product builders get a uniform DCAT-AP record shape contributed by hundreds of catalogues; see developers builders use cases. Journalists, academics and students cite national publications with the publishing institution named on the record.

What should I know before requesting a sample?

Four things, stated plainly.

First, this is a discovery layer. The portal holds descriptions and identifiers; each underlying dataset lives with its publisher. A sample from Datadory means resolved records rather than a pointer list - but the grain beneath is the publishers', not ours.

Second, match counts swing enormously with phrasing. The exact phrase returned 28 records; the unquoted equivalent matched roughly 54,000 through fuzzy matching. Scope the terms first, then read result.count to see what each variation bought you.

Third, recency varies record by record. One-off publications sit beside maintained multi-decade series, sometimes within the same result set. Read accrual_periodicity per record instead of assuming a common rhythm.

Fourth, the score reflects the job. Datadory rates this record 6 out of 10 against a catalog mean of 7.81 - excellent breadth, modest depth on any single topic. When a question needs one authoritative series rather than wide discovery, pair this with Eurostat Comext at 9/10 or the Federal Reserve's G.17 at the same grade. The sample shows the terrain unchanged, caveats included.

What else sits in Datadory's industrial-gases catalog?

Of the 1,744 datasets Datadory catalogs across 159 viable industries, eight cover industrial gases, and this portal is the widest-discovery entry among them. The companions:

Browse the industrial gases data hub for the full slice, or see the best industrial-gases datasets ranking.

Field dictionary

Every field below is documented against real records. The full dictionary ships with the sample.

Field dictionary - the eight documented fields on every matched record
fieldtypedefinitionexample
result.countintegerTotal number of dataset records matching the query - the number that tells you whether you are looking at a slice or a haystack.28
result.results[].titletextMultilingual map of dataset titles keyed by ISO language code, so a Dutch-language record still answers an English-language query.Emissies naar lucht op Nederlands grondgebied; stationaire bronnen, 1990-2021
result.results[].descriptiontextAbstract of the dataset written by the publishing portal, carried in the same keyed-by-language map structure as the title.description.en / description.nl
result.results[].catalogtextThe contributing catalogue as an object: identifier, title, homepage and publisher of the portal that supplied the record.opendataportal.at
result.results[].countrystringCountry of the publishing portal - the fastest cut for splitting a European-wide sweep into per-market reads.Austria
result.results[].distributions[].format.labelstringFile format of each attached distribution as an EU authority label; one record can carry several distributions in different formats.PDF
result.results[].accrual_periodicityenumUpdate rhythm the publisher declares for the dataset - one-off publications sit beside annually or monthly maintained series.annual
result.results[].is_hvdbooleanWhether the record is flagged as a high-value dataset under the EU's high-value dataset rules - a ready-made importance filter.true

data.europa.eu — EU open data portal - product specification

AttributeValue
IndustryIndustrial Gases
Records~1.9 million harvested dataset records portal-wide
Industry matches28 exact matches for “industrial gases”; ~54,000 loose matches unquoted
Fields8 core fields per record; 2 further distribution-level elements folded under additional fields on request
Formats observedPDF, HTML, CSV, JSON, Excel XLSX, XML, RDF-Turtle, Atom
Geographic coverageEU member states, EFTA, EU institutions and agencies
Temporal coverageVaries per underlying dataset - one-off publications alongside series reaching the 1990s
GranularityOne metadata record per dataset; underlying grain from national tables to facility-level inventories
Quality6/10 on the catalog rubric (mean 7.81); definitions verified against live responses
DeliveryAPI, files, or your warehouse - daily, weekly, or hourly

What teams do with it

  • European regulatory-landscape mapping National inventory reports and emissions tables surface country by country, giving market-entry teams the compliance paperwork trail around gas-consuming industry before they commit.
  • Emissions baselining for energy-intensive sectors Stationary-source air-emissions series such as the Dutch 1990-2021 table put three decades of facility-side environmental context behind any industrial-gases demand story.
  • Country screening and territory ranking The country field splits a pan-European query into per-market reads, so twenty-seven candidate markets collapse into a ranked shortlist without twenty-seven separate searches.
  • High-value dataset monitoring The is_hvd flag separates records the EU itself designates as high-value from the long tail - a one-column importance filter most users never think to apply.
  • Citation-grade sourcing Every record names its publishing portal and catalogue, so figures survive due diligence with provenance attached rather than a dead-end citation.

Questions buyers ask

How many records match “industrial gases”?

28 records for the exact phrase at verification, drawn mainly from national portals. Looser unquoted matching fans out to roughly 54,000 records, which is why scoping the phrase matters more than paging through results.

What kinds of records turn up in the industrial-gases slice?

National inventory reports, stationary-source air-emissions tables, industrial-registry extracts and classification indices. Verified examples include Austria's 2008 national inventory report, a Spanish national classes index in four formats, and a Dutch air-emissions series covering 1990-2021.

Does the portal hold the underlying data itself?

No. It is a discovery layer operated by the Publications Office of the European Union: every record describes a dataset that remains on the national or EU portal that published it, complete with that catalogue's identifiers so descriptions and actual tables never get confused.

Which countries contribute records?

EU member states, EFTA countries and EU institutions and agencies, in whatever shape their portals publish. The verified industrial-gases slice drew on Austrian, UK, Spanish and Dutch catalogues, illustrating the usual pattern: one query, several national administrations.

How current are the records?

Currency is a per-record property. Each record carries the publisher's declared maintenance rhythm and modification dates, and the range is wide - one-off publications sit beside maintained series such as the Dutch emissions table spanning 1990-2021. Read accrual_periodicity per record rather than assuming a common rhythm.

What does the high-value dataset flag mean?

is_hvd marks records falling under the EU's high-value dataset rules - categories the Union designates as having outsized reuse potential. In practice it works as a one-column importance filter: flagged records clear a bar set by policy, not by keyword luck.

Can a sample be scoped to specific countries or formats?

Yes. Name the countries, formats or record types you care about and the sample arrives shaped to that scope, with the full field dictionary attached and any additional fields you requested populated. Samples precede any commitment, and the schema you test is the schema you ship against.

How does this compare with Eurostat Comext for gas-industry work?

Different jobs. This portal discovers the terrain - reports, registries, emissions tables across every European administration. Comext measures one thing precisely: monthly EU trade in goods by product code back to 1988, rated 9/10. Analysts typically start here to find what exists, then move to Comext or the Fed's G.17 for the measurable series.

Notes on this record

  • Discovery layer, stated plainly The portal holds descriptions, not the tables themselves - each record points home to the portal that published it. Datadory resolves records so your sample arrives as rows, not errands.
  • Exact beats loose, by four orders of magnitude The quoted phrase returned 28 records; unquoted matching fanned out to roughly 54,000. Scope the terms first, page second - breadth comes from varying vocabulary, not from paging deep.
  • Freshness is a per-record property Many harvested records declare a one-off publication with no maintenance rhythm at all, while neighbours carry maintained multi-decade series. Read accrual_periodicity before treating any record as current.
  • Scored mid-catalog, on purpose Datadory scores this record 6/10 against a catalog mean of 7.81 - breadth of discovery rather than depth of any one series is the job here, and the scoring says so.
  • Pair it with a real series Eurostat Comext carries monthly EU trade in goods by product code back to 1988 and scores 9/10; the Fed's G.17 covers US industrial production at the same grade. Use this record to find the terrain, those to measure it.

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