Find data by science case

Start from the measurement, not the facility. Each route names the archive, what it offers for that case, and where useful a minimal Python query.

Time-series photometry of a star

Light curves for transits, eclipsing binaries, stellar variability, flares and asteroseismology.

TESS light curves (opens in a new tab)
Near-all-sky coverage at 20 s to 30 min cadence, ~27 d per sector with multi-year baselines near the ecliptic poles. QLP light curves cover stars brighter than T = 13.5.
How TESS data is organised
Python
```
import lightkurve as lk
lk.search_lightcurve("TIC 25155310", mission="TESS").download_all()
```
Kepler and K2 light curves (opens in a new tab)
Four years of near-continuous 30 min (and 1 min) photometry of ~150,000 stars in one 115 deg² field; about three months per K2 campaign along the ecliptic.
How Kepler / K2 data is organised
ZTF light curves (opens in a new tab)
Sparse g, r, i light curves to r ≈ 20.5 across the sky north of Dec −30°, with the public survey revisiting about every two nights since 2018.
How ZTF data is organised
Gaia epoch photometry (opens in a new tab)
Sparse (tens of epochs per source) but millimagnitude-precise over years. DR3 has G, BP, RP series for 10.5 million variables; DR4 adds per-transit epoch photometry as its own table.
How Gaia data is organised

Parallax, proper motion, radial velocity, broadband photometry and stellar parameters.

Gaia DR3 (opens in a new tab)
The astrometric reference: positions for 1.8 billion sources, parallaxes and proper motions for 1.46 billion, plus G, BP, RP photometry and astrophysical parameters.
How Gaia data is organised
Python
```
from astroquery.gaia import Gaia
Gaia.query_object_async("Proxima Cen", radius="10 arcsec")
```
SIMBAD (opens in a new tab)
Identifiers, cross-identifications, basic data and the literature for a named object.

Optical spectra, spectroscopic redshifts and emission-line measurements.

DESI data releases (opens in a new tab)
R ≈ 2000–5500 spectra and Redrock redshifts for more than 18 million galaxies, quasars and stars in DR1, over a ~14,000 deg² survey.
How DESI data is organised
SDSS (opens in a new tab)
Over two decades of spectra (SDSS, BOSS, eBOSS, SDSS-V), queryable through CasJobs and SkyServer SQL.
How SDSS data is organised
SPARCL (opens in a new tab)
One interface to DESI, SDSS and BOSS spectra by position or ID, returning arrays rather than files.

Survey imaging from radio to gamma rays on a common grid, with catalogue overlays.

Aladin Lite (opens in a new tab)
Hundreds of HiPS surveys from Planck to Euclid in one browser viewer, with VizieR catalogue overlays.
ESASky (opens in a new tab)
HiPS imagery plus footprints of individual pointed observations from ESA, NASA and ground archives.
NASA SkyView (opens in a new tab)
FITS cutouts from dozens of surveys, resampled to a common projection and pixel scale.
Legacy Surveys viewer (opens in a new tab)
g, r, z (and i) imaging over more than 20,000 deg² in DR10, with unWISE photometry; DESI's target-selection imaging.

Event lists, spectra, light curves and source catalogues from X-ray missions.

HEASARC (opens in a new tab)
One query across the high-energy archives of nearly every NASA mission and several partner missions.
Chandra Source Catalog (opens in a new tab)
Positions, fluxes, hardness ratios and variability for over 400,000 X-ray sources.
How Chandra data is organised
eROSITA DR1 (opens in a new tab)
The deepest all-sky survey in the 0.2–2.3 keV band, for the Galactic hemisphere 180° < l < 360°.
How eROSITA data is organised

Calibrated strain, event catalogues, posterior samples and sky localisations.

GWOSC (opens in a new tab)
Calibrated strain for whole observing runs, GWTC catalogues and posterior samples, with notebook tutorials.
How LIGO data is organised
Python
```
from gwpy.timeseries import TimeSeries
TimeSeries.fetch_open_data("L1", 1126259446, 1126259478)
```
GraceDB (opens in a new tab)
Low-latency candidates with false-alarm rate, source classification and HEALPix sky maps, within minutes.
How LIGO data is organised

Masses, radii, orbital elements and host properties, with the solution each comes from.

NASA Exoplanet Archive (opens in a new tab)
Every confirmed planet, with every published parameter set and a TAP service for queries.
ExoFOP (opens in a new tab)
TESS Objects of Interest with community follow-up: imaging, reconnaissance spectroscopy, radial velocities.
How TESS data is organised

Temperature and polarisation maps, component-separated foregrounds and likelihood codes.

Planck Legacy Archive (opens in a new tab)
Final frequency maps at 30–857 GHz, component-separated CMB and foreground maps, and the likelihoods.
How Planck data is organised
LAMBDA (opens in a new tab)
NASA's CMB archive: WMAP, Planck mirrors, suborbital and ground experiments, and analysis tools.
How WMAP data is organised

Supernovae, tidal disruption events, gamma-ray bursts and other transients, as reported.

Transient Name Server (opens in a new tab)
The IAU's official naming and classification register for new transients.
Rubin alert brokers (opens in a new tab)
Rubin's alert stream, up to ~10 million alerts a night, reaches users through brokers such as ALeRCE, Fink and Lasair, each with its own classifiers and filters.
How Rubin data is organised
General Coordinates Network (opens in a new tab)
Machine-readable notices and circulars from gamma-ray, X-ray, neutrino and gravitational-wave facilities.

Continuum surveys and archival interferometer observations.

VLA Sky Survey (opens in a new tab)
2–4 GHz imaging at 2.5″ resolution of the sky north of Dec −40°, in repeated epochs.
How VLA data is organised
LOFAR Two-metre Sky Survey (opens in a new tab)
120–168 MHz at 6″ resolution and a median 83 µJy/beam, sensitive to steep-spectrum and diffuse emission.
How LOFAR data is organised
NRAO archive (opens in a new tab)
Raw visibilities and pipeline-calibrated data from the VLA, VLBA and GBT.
How VLA data is organised