Data.gov - Semiconductor Datasets Catalog

The index card drawer for the entire United States government's data output. Data.gov - Semiconductor Datasets Catalog is a cut of Data.gov's federated catalog - 552,271 datasets available at time of research - filtered to where the word semiconductor actually leads: NIST CHIPS for America award and program data, USGS mineral commodity summaries covering the silicon, gallium and germanium feedstocks chips depend on, Department of Energy national-lab research outputs, and Commerce export-control references.

Records arrive harvested from agency feeds under full DCAT-US metadata, so every one resolves back to its owning agency page and raw files in CSV, JSON, XML plus XLS, ZIP, KML and HTML. What Datadory does is turn that interactive discovery layer into a delivered dataset: normalized rows, stable join keys, your cadence - instead of a search box you have to re-query every time a question changes.

The delivered shape is one row per catalog record, carrying what a researcher actually needs to triage a hit:

title              : <official dataset title>            # as submitted by the publishing agency
publisher          : <agency or organization>           # e.g. NIST, USGS, DOE national lab
identifier         : <unique catalog id>                # join key back to the full record
last_updated       : <YYYY-MM-DD>                       # 'Dataset Last Updated' on the result card
resource_formats   : CSV, JSON, XML                     # XLS, ZIP, KML, HTML also appear
catalog_checked    : <timestamp>                        # most recent harvest validation

Three conventions in that block decide whether a pipeline survives contact with real data. Two timestamps travel on every record and they are not the same thing - last_updated is the publishing agency's own change date while catalog_checked is the catalog's verification sweep, and conflating them produces freshness claims no source ever made. The publisher field is where the analytical leverage sits: grouping semiconductor hits by it instantly separates incentive-program records (NIST) from feedstock-supply records (USGS) from research outputs (DOE). And resource_formats stays multi-value because real records list several distributions at once. Live values for the agencies and programs you care about arrive with your sample.

Nine fields anchor the dictionary, each carrying one axis of the record - what it is called, who published it, how fresh it is, and in what formats the underlying files exist.

Three chips summarize the footprint:

• Geography — United States federal government, with some state, tribal, university and non-profit harvested sources mixed into the same shelf, separable by organization type once delivered.
• Time — continuously harvested from agency feeds; individual records run from static historical series through daily refreshes depending on the contributing agency, so the catalog holds both decades-old series and this-week entries side by side.
• Granularity — one record per cataloged dataset; underlying granularity varies entirely by the contributing agency, from facility-level lists to national annual totals.

That third chip sets expectations honestly. This is metadata about datasets that may describe matter, money or regulation - which is exactly why it pairs so well with the measurement-heavy siblings in the slice. The catalog's own scale is the headline: 552,271 records at time of research, with the semiconductor subset concentrated among NIST, DOE, USGS and Commerce publishers.

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

You choose the channel and the cadence; keeping pace with a continuously harvested catalog is our problem, not your cron job. The two-timestamp convention above travels fixed across all three channels, so a nightly warehouse load and an on-demand lookup agree row for row on which date means what. When an agency adds records or refreshes existing ones, the feed you consume stays normalized - same columns, same types, same join keys - rather than arriving as whatever shape the harvest returned that morning. A sample scoped to the agencies, programs and keywords you name ships first either way, sized to test in your own pipelines the day it lands.

Four workloads lean on this cut hardest:

1. Competitive intelligence & product teams — track which companies and universities hold CHIPS for America awards and how program records evolve, then read the funding landscape around their own supply positions without hand-building agency watchlists.
2. Supply-chain and critical-minerals analysts — pair USGS mineral commodity summaries for silicon, gallium and germanium against their bill-of-materials exposure to see where the US government itself documents feedstock concentration risk.
3. Policy researchers and trade teams — Commerce export-control references sit in the same shelf as the research outputs they regulate, making the catalog one of the few places policy and technology records can be pulled together on shared axes.
4. Journalists, academics and students — citable specifics attributed to named agencies: which program, which publisher, which update date - with the verification timestamp attached so a fact's provenance is checkable, not asserted.

Quant and investment teams round it out, using award-record velocity as an alternative signal for regional semiconductor buildout activity ahead of revenue data.

Competitive intelligence and product teams get the federal money-and-regulation layer behind competitor announcements - who holds awards, which programs are live, what changed this month. Market researchers and consultants get government-published baseline documents for sizing semiconductor materials and equipment demand without paying dashboard tolls for facts agencies publish themselves. Journalists, academics and students get named publishers and verifiable timestamps behind every claim. Data scientists and ML engineers get a tidy corpus of DCAT-US metadata for building document-classification or entity-resolution systems over the federal catalog. All delivered daily, weekly, or hourly.

Provenance note - the catalog is maintained by the U.S. General Services Administration under the Data.gov program. Datadory keeps the source name on the record; field definitions above were mapped against the documented record structure during the August 2026 research pass.

Completeness note - the 552,271 figure is the catalog's advertised total, not a count of semiconductor matches; the exact semiconductor-matching population was not confirmable at research time because the landing page serves the default view rather than filtered results. Treat any count we quote in a delivered extract as measured, and any count quoted elsewhere as approximate.

Dictionary note - nine core fields are verified. Derived conveniences (split multi-value format lists, separated agency-parent/child names, parsed temporal coverage from the DCAT-US object) fold under additional fields on request and get pinned down against a delivered extract before anything depends on them.

Where to go next - the rest of the Semiconductor Materials & Equipment shelf puts substance behind these pointers: patent corpora for the R&D layer, fab lists for physical capacity, and billings statistics for market dollars - plus the head-to-head that weighs this paperwork against computed physics.