juliensimon/jwst-observations

JWST Observation Catalog

Credit: NASA/Desiree Stover

Part of a dataset collection on Hugging Face.

Dataset description

The JWST Observation Catalog is a complete index of every observation obtained by NASA/ESA/CSA's James Webb Space Telescope, drawn from the Mikulski Archive for Space Telescopes (MAST). Launched on December 25, 2021 and commissioned in mid-2022, JWST is the most powerful infrared space observatory ever built, operating at the Sun–Earth L2 Lagrange point with a 6.5-meter segmented primary mirror and four science instruments: NIRCam, NIRSpec, NIRISS, MIRI, and the FGS fine guidance sensor.

Each row in this catalog is one JWST observation — a unit of telescope time executing a single exposure sequence with a specific instrument, filter, target, and pointing. Rows include the proposal under which the observation was taken (proposal ID, PI, title, category: GO, GTO, ERS, or DDT), the target (name, coordinates, type, moving/fixed flag, redshift for extragalactic targets), the instrument and observing mode (imaging, slit/slitless spectroscopy, integral field, coronagraphy), timing (start/end MJD and ISO date, total on-source exposure), wavelength coverage (micrometers), filters used, the CAOM data product types produced, and the maximum calibration level available.

This dataset is the canonical source for answering questions like: what has JWST observed near a given RA/Dec? What proposals used the MIRI coronagraph? How much exposure time has been spent on a particular target? When does an exclusive-access dataset become public? It is designed for cross-matching with target catalogs (quasars, exoplanets, galaxies, solar system bodies), for program-level summaries, and for planning cross-facility follow-up observations. It complements the Chandra, eROSITA, Fermi, and other space telescope catalogs in this collection, giving a uniform tabular view of the modern high-energy-to-infrared space observatory fleet.

The catalog is derived from MAST's CAOM (Common Archive Observation Model) tables — specifically dbo.caomobservation joined with dbo.caomplane — and is refreshed weekly as JWST pipeline products flow through the archive. Calibration and engineering observations are included but are distinguishable via the intent column.

This dataset is suitable for tabular classification tasks.

Schema

Column	Type	Description	Sample	Null %
obs_id	string	MAST observation identifier (e.g., 'jw01011002001_02101_00001_mirifulong'); encodes proposal, visit, exposure, and detector. Primary key.	jw09016001002_07101_00003_nrs1	0.0%
obstype	string	CAOM observation type code: 'S' (simple), 'C' (composite). Most JWST observations are simple.	S	0.0%
intent	string	Observation intent: 'science' or 'calibration'	science	0.0%
proposal_id	string	JWST proposal identifier (string, e.g., '1011'); groups related observations by Principal Investigator's program	9016	0.0%
proposal_pi	string	Last name, first initial of the proposal Principal Investigator	Stark, Daniel P.	0.0%
proposal_title	string	Full title of the JWST observing proposal	Galaxy Formation at The Redshift Fron...	0.0%
proposal_project	string	Proposal project code (e.g., 'GO', 'GTO', 'ERS', 'DDT'); GO = General Observer, GTO = Guaranteed Time, ERS = Early Release Science, DDT = Director's Discretionary Time	GO	0.0%
proposal_keywords	string	Science keywords tagged on the proposal (semicolon-separated)	VISITSTATUS=IMPLEMENTATION	96.4%
target_name	string	Target name as provided by the proposer (may include survey designations, coordinates, or informal names)	GO9016_apt_v2	0.0%
target_ra	float64	Target right ascension in decimal degrees (ICRS). May be 0 for moving or calibration targets.	53.08809291666666	0.0%
target_dec	float64	Target declination in decimal degrees (ICRS). May be 0 for moving or calibration targets.	-27.87126388888891	0.0%
target_moving	bool	True if the target is a moving solar system body (asteroid, comet, planet, moon); False for fixed celestial targets	False	0.0%
observation_start_mjd	float64	Observation start time as Modified Julian Date (earliest plane). Null if no plane has timing.	61335.35575572916	3.6%
observation_end_mjd	float64	Observation end time as Modified Julian Date (latest plane)	61335.45808057871	3.6%
total_exposure_sec	float64	Sum of on-source exposure times across all planes for this observation, in seconds	17506.668	0.0%
wavelength_min_meters	float64	Minimum wavelength covered across all planes, in meters (e.g., 6.0e-7 = 0.6 microns)	1.66e-06	0.9%
wavelength_max_meters	float64	Maximum wavelength covered across all planes, in meters	5e-06	0.9%
filters	string	Semicolon-joined list of distinct bandpass/filter names used across planes (e.g., 'F200W;F356W')	F170LP;G235M	0.1%
dataproduct_types	string	Semicolon-joined list of distinct CAOM data product types: 'image', 'spectrum', 'cube', 'measurements'	image;spectrum	0.0%
max_calibration_level	Int64	Highest CAOM calibration level available for this observation (0 = raw, 1 = telemetry, 2 = calibrated, 3 = science-ready, 4 = higher-order products)	2	0.0%
plane_count	Int64	Number of distinct planes (data products at different calibration levels) for this observation	2	0.0%
earliest_release_date	string	Earliest public release date across planes (ISO-8601); exclusive-access observations become public at this date	2027-10-23T07:47:36Z	3.6%
instrument	string	Instrument name: NIRCAM, NIRSPEC, NIRISS, MIRI, or FGS (from 'INSTRUMENT/MODE' split)	NIRSPEC	0.0%
observation_mode	string	Observation mode: IMAGE, SPECTRUM, IFU, SLIT, WFSS, TACQ, etc. (from 'INSTRUMENT/MODE' split)	MSA	0.8%
observation_start_date	string	Observation start time as ISO-8601 UTC datetime (derived from MJD)	2026-10-22T08:32:17Z	3.6%
observation_end_date	string	Observation end time as ISO-8601 UTC datetime (derived from MJD)	2026-10-22T10:59:38Z	3.6%

Quick stats

• 999,567 JWST observations
• 909,871 science, 89,696 calibration
• 2,078 distinct proposals
• 677,352 total on-source exposure hours
• Date range: 2022-01-28 to 2026-10-22

Usage

from datasets import load_dataset

ds = load_dataset("juliensimon/jwst-observations", split="train")
df = ds.to_pandas()

from datasets import load_dataset

ds = load_dataset("juliensimon/jwst-observations", split="train")
df = ds.to_pandas()

# Science observations only
sci = df[df["intent"] == "science"]

# All NIRCam imaging on a specific target (cone search ~5 arcmin)
import numpy as np
target_ra, target_dec = 189.998, 62.183  # Hubble Deep Field North
sep = np.hypot(sci["target_ra"] - target_ra, sci["target_dec"] - target_dec)
nearby_nircam = sci[(sep < 0.08) & (sci["instrument"] == "NIRCAM") & (sci["observation_mode"] == "IMAGE")]
print(f"Found {len(nearby_nircam)} NIRCam images near HDF-N")

# Instrument usage over time
import matplotlib.pyplot as plt
sci["start_date"] = __import__("pandas").to_datetime(sci["observation_start_date"])
sci.groupby([sci["start_date"].dt.to_period("M"), "instrument"]).size().unstack().plot.area(figsize=(12, 5))
plt.ylabel("Observations per month")
plt.title("JWST instrument usage over time")
plt.show()

# Sky coverage (equatorial)
sky = sci[(sci["target_ra"] > 0) | (sci["target_dec"] != 0)]
plt.figure(figsize=(12, 6))
plt.scatter(sky["target_ra"], sky["target_dec"], s=0.5, alpha=0.3)
plt.xlabel("RA (deg)"); plt.ylabel("Dec (deg)")
plt.gca().invert_xaxis()
plt.title("JWST target sky distribution")
plt.show()

Data source

https://archive.stsci.edu/

Update schedule

Weekly (Monday at 13:00 UTC) via GitHub Actions.

Related datasets

• juliensimon/chandra-x-ray-sources

• juliensimon/erosita-erass1-xray

• juliensimon/4xmm-dr14-xray-sources

• juliensimon/nasa-exoplanets

• juliensimon/quasar-catalog

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About the author

Created by Julien Simon — AI Operating Partner at Fortino Capital. Part of the Space Datasets collection.

Citation

@dataset{jwst_observations,
  title = {JWST Observation Catalog},
  author = {Simon, Julien},
  year = {2026},
  url = {https://huggingface.co/datasets/juliensimon/jwst-observations},
  note = {Derived from MAST, Space Telescope Science Institute, https://archive.stsci.edu/},
  publisher = {Hugging Face}
}

License

CC-BY-4.0