Data.gov Catalog - Furniture Search - 30 Matched US Government Records

A discovery layer, not a subject dataset - and that distinction decides how you use it. Where a conventional dataset hands you observations in one shared table, this record hands you the 30 datasets the US government's master catalog surfaces for the query 'furniture', selected from 552,271 indexed entries at the August 2026 research pass. The publishers span every tier of American government: a federal fire laboratory (NIST), a cultural agency (the National Endowment for the Arts), a county surplus market (King County, Washington), big-city procurement shops (Los Angeles, Chicago) and the General Services Administration.

Each result arrives as a card with the fields buyers actually triage on - title, publishing organization, last-updated date, abstract snippet, format badges, a numeric relevance score, prior-month view counts and a catalog verification timestamp - and each card opens into a full detail record beneath it. Results can be reordered by relevance, popularity or publication date and filtered by geography, keyword, organization type and geospatial status.

Within Datadory's catalog of 1,744 datasets across 159 viable industries this record scores 6/10 for quality with field definitions verified during research. Narrow by design, unmatched on coverage: nothing else in the homebuilding slice reaches product-safety evidence and public-sector procurement in one pull.

Four ranked results from the August 2026 research pass, flat exactly as the fields arrive:

# Row 1 - a federal fire lab's upholstery experiments, top of the ranking
rank                 : 1
title                : Data from "Full-Scale Experiments to Demonstrate Flammability Risk of Residential
                       Upholstered Furniture and Mitigation Using Barrier Fabric"
organization         : National Institute of Standards and Technology
dataset_last_updated : 2021-03-17
formats              : EXCEL
identifier           : ark:/88434/mds2-2379

# Row 2 - an agency counting its own chairs, desks and dollar values
rank                 : 2
title                : Knoll Furniture Inventory
organization         : National Endowment for the Arts
dataset_last_updated : 2019-05-30
description          : Physical inventory record of the agency Knoll furniture collection.
                       Lists locations, quantities, dollar values.
formats              : html

# Row 3 - a county government moving surplus stock
rank                 : 5
title                : FMD "New To You" Market Furniture List
organization         : King County, Washington
dataset_last_updated : 2023-06-08
formats              : json, xml, csv

# Row 4 - the companion burn-test study
rank                 : 6
title                : Data from "Flaming Tests on Upholstered Chair Mock-Ups"
organization         : National Institute of Standards and Technology
dataset_last_updated : 2021-03-17

# catalog totals - the funnel in two numbers
indexed_catalog_wide : 552271
furniture_matches    : 30

The rows settle the questions a buyer asks first. Breadth: a federal laboratory, a cultural agency and a county government sit three ranks apart, so one query covers safety science, asset accounting and secondary markets at once. Recency spread: revision stamps run from May 2019 to June 2023 among these four, and from 2019 to 2026 across the full match set, so vintage labeling matters row by row. Substance: the Knoll card carries a real abstract - locations, quantities, dollar values - which is how you tell an inventory from a pamphlet before committing.

Nine documented columns, definitions verified during research, in three families. Identity: title, the card's printed label; Organization, the publishing agency that doubles as a tier marker between a federal lab and a county market; and identifier, the persistent handle such as NIST's ARK string. Freshness and trust: Dataset Last Updated, the revision stamp whose furniture-match values run 2019 through 2026; and Catalog Last Checked, the timestamp of the catalog's latest verification pass, which lets a stale entry announce itself. Substance and demand: description, the abstract in full; formats, the badge set (html, csv, json, xml and xls appear across the matches); Search relevance, the scored closeness the default sort orders by; and Views last month, a demand signal most catalogs never publish.

Read together, the nine answer what a record is, who stands behind it, how fresh it is and whether anyone else is reading it - the whole triage decision, before a single underlying table is opened.

The result card is the summary layer; a fuller detail record sits underneath each match and rides along at sampling:

• Detail-level catalog metadata - agency bureau codes and program codes, issue and revision dates, keyword tags, language and the complete publisher hierarchy.
• Contact-point fields - the responsible desk recorded on each entry, with its address fields.
• Scholarly cross-references - the DOI citations some records carry in their reference lists.
• Sort and filter dimensions across the wider result set - relevance, popularity and publication-date ordering, plus geography, keyword, organization-type and geospatial filters.

Name any of these when you request the sample and they land in the same row shape - no second schema, no re-plumbing on your side.

Geography - the United States across all four government tiers. Federal publishers lead the ranking, but state, county and city entries sit in the same result set: King County, Washington moves surplus furniture, while Los Angeles and Chicago publish procurement and auction metrics. A national safety question and a municipal purchasing question draw from one record.

Temporal - layered rather than single-dated. Each row carries its own revision stamp, and across the 30 furniture matches those stamps span 2019 to 2026; the catalog separately prints when it last verified each harvested record. Mixing vintages is normal here, and the two date columns make it explicit rather than silent.

Granularity - one catalog entry per dataset: 30 rows, each opening into its own detail record. There is no shared observation table underneath, which is precisely why this record pairs well with a tabular neighbor - it tells you what exists and who holds it, and the neighbors supply the measurements.

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

Name the scope when you request the sample - the full 30-row pull, just the NIST flammability pair, or the procurement-and-auction subset. The sample ships first either way; the recurring feed lands on whatever cadence your models and dashboards need, shaped to the scope you named rather than dumped whole.

Nine verified columns and a deliberately narrow match set earn their keep in six jobs:

• Product-safety and flammability research - NIST's full-scale upholstered-furniture experiments and the chair mock-up burn tests replace anecdote with measured fire behavior.
• Standards and code advocacy - the barrier-fabric mitigation results quantify what a material substitution buys, in numbers that survive a comment letter.
• Procurement and asset-disposition benchmarking - GSA auction records beside Los Angeles and Chicago procurement metrics show how public agencies buy, value and move furniture; the pattern extends competitor-tracking work into the public sector.
• Facilities and asset-register design - the Knoll inventory's locations-quantities-values structure is a working template for corporate asset registers.
• Citation-grade research - organizations, revision dates and persistent identifiers on every row, the same discipline behind citation-grade research.
• Adjacent-market discovery - patent records in the result set surface furniture-relevant IP activity retail-side datasets never reach.

Market Researchers & Consultants get a government-wide furniture sweep in one pass - safety, inventory and procurement angles without thirty separate hunts. Journalists & Academics get named agencies, dated revisions and persistent identifiers, which is what makes a citation checkable. Competitive Intel & Product Teams get compliance context - flammability evidence and procurement norms - to set beside retail benchmarks. Data Scientists & ML Engineers get thirty clean catalog rows carrying relevance scores and view counts, a tidy little corpus for entity-resolution and deduplication work. Start from the homebuilding data hub, then read the persona cuts for market researchers, journalists & academics and competitive intel product teams.

Provenance note - compiled from the master catalog the US federal system uses to index participating agencies' metadata, harvested from the agencies' own published records. One editorial layer across every tier of government is why a NIST experiment and a county surplus list read consistently in the same frame.

Classification note - the furniture trade itself sits in NAICS 442, and the NAICS 442 furniture and home furnishings stores glossary entry draws that retail boundary in plain language; this record supplies the government-side context around the trade.

Completeness note - Datadory scores this record 6/10 with field definitions verified during research and four real sample rows shipping with it. The honest caveat is heterogeneity: thirty records running from combustion science to auction lots reward teams who arrive knowing what they are fishing for, and reward them unusually well.

Where to go next - the community-corpus complement: 77 machine-learning datasets matching the same query, from image-classification sets to interior-design imagery, one click away in the related rail below.