hepdata

name

hepdata

description

Use when the user wants the numerical tables, ROOT files, or YAML data attached to a published HEP measurement, identified by HEPData submission ID (`ins1234567`, `123/v2`), INSPIRE record id, paper DOI, or paper title — typically because they want to re-fit, plot, or run systematics studies on the published measurement. Routes to https://www.hepdata.net/ via WebFetch and the HEPData REST API. Returns table URLs (YAML, ROOT, CSV) suitable for downstream `pyhf`, `pandas`, or `uproot`. Does NOT cover the paper's narrative or the headline measured value (use `read-publication`), PDG canonical constants (use `pdg-lookup`), or Open Data primary datasets (use `cern-opendata` or `atlas-opendata`). Disambiguator phrase: HEPData published-tables retrieval.

hepdata — published HEP tables for re-fitting

HEPData hosts the numerical tables, covariance matrices, and ROOT inputs that LHC papers publish alongside their results. Use this skill when the user wants to consume those tables (re-fit, plot, systematics study) — not when they want the headline measurement value (that's read-publication).

Scope

Load this skill when the user provides any of:

• A HEPData submission id (ins1234567 — INSPIRE-keyed, or 123/v2 — HEPData-internal versioned id)
• An INSPIRE record id (recid:1234567 or inspire-hep:1234567)
• A paper DOI (10.1103/..., 10.1007/JHEP...)
• A paper title (exact match preferred — HEPData search is fuzzy)

…and they want the tabulated data, not the prose result.

Do NOT load this skill for:

• The headline measured value or the paper narrative → read-publication.
• PDG canonical constants → pdg-lookup.
• Open Data primary datasets (CMS / ATLAS / LHCb data releases on opendata.cern.ch) → cern-opendata.
• ATLAS Monte Carlo metadata by DSID → atlas-opendata.

HEPData URL patterns

Pattern	Meaning
https://www.hepdata.net/record/ins<inspire-recid>	INSPIRE-keyed (most common)
https://www.hepdata.net/record/<hepdata-id>	HEPData-internal id
https://www.hepdata.net/record/ins<id>?version=N	Specific version
https://www.hepdata.net/record/ins<id>?format=json	Machine-readable record metadata
https://www.hepdata.net/search/?q=<query>&format=json	Search by title / DOI / keyword

INSPIRE → HEPData mapping

If the user gives you an INSPIRE recid, the HEPData URL is https://www.hepdata.net/record/ins<recid>. This is 1:1 by construction.

If the user gives you a DOI or title, resolve it to an INSPIRE recid first via the read-publication retrieval recipe (or run INSPIRE search yourself), then build the HEPData URL.

Choosing a format

Each HEPData record exposes its tables in multiple formats. Pick by use case:

Format	URL suffix	When to use
YAML	?format=yaml (per-table)	Most portable; human-readable; pyhf-friendly
ROOT	?format=root	When the user works in ROOT / uproot already
CSV	?format=csv	Quick pandas.read_csv integration
JSON	?format=json	Programmatic record introspection

Default recommendation: YAML for new analysis pipelines, ROOT for ATLAS- internal habits.

Retrieval recipe

1. Resolve the input to an INSPIRE recid or HEPData id.
2. WebFetch https://www.hepdata.net/record/ins<recid>?format=json to get the record metadata. Look at:
   • data_tables[].name and .description to pick the right table(s).
   • data_tables[].data for the per-table data URL.
3. Return per-table URLs to the user with table names and descriptions.
4. Suggest the right downstream pipeline (pyhf for likelihoods, pandas.read_csv for tabular extraction, uproot.open for ROOT inputs).

Common downstream pipelines

After retrieving HEPData tables:

• Re-fit a likelihood → use pyhf if the record exposes workspace.json (HistFactory standard; ATLAS publishes these for many measurements).
• Plot a spectrum → pandas.read_csv + matplotlib / mplhep.
• Combine with another measurement → covariance matrices are usually in a separate table; flag this to the user.

Failure recovery

• HEPData has no record for an INSPIRE recid → not every paper publishes to HEPData. Tell the user; offer to extract the value from the paper via read-publication instead (lossy: just the published number, no uncertainties propagated).
• Search returns multiple records → present top 3 hits with title + experiment + year, ask the user to disambiguate.
• A specific format isn't available for a table → fall back to YAML (always available).