imagesartmuseumsmetadatacultural-heritageimage-metadataglobalpaintingsphotographypublic-domain

Museum Artwork and Image Metadata

1400–2024

Free

Open dataset

Sample structure: 97.9 / 100

4 download links issued

Seller: waseemahmad

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Source, license and coverage

Supplier documentation. These claims are separate from the automated sample score. A listing edit date is not a data freshness date.

License: Not documented — confirm reuse terms with the seller
Source / creator: Supplier-cited: Metropolitan Museum of Art; Art Institute of Chicago; Rijksmuseum; Smithsonian
Collection method: uploaded
Coverage / snapshot: 1400–2024
Data last updated: Not documented
Update schedule: Not documented

Source documentation ↗

Source attribution is supplier-reported. The source link identifies publisher documentation; it does not independently verify this uploaded extract. Other cited publishers: Art Institute of Chicago: https://api.artic.edu/docs/; Rijksmuseum: https://data.rijksmuseum.nl/; Smithsonian: https://www.si.edu/openaccess

Sample structure score: 97.9 / 100

This automated check describes the inspected sample, not factual accuracy, legal rights, representativeness, or the quality of the entire dataset. It is not a customer rating.

Assessed 10 sample records (CSV) on 2026-10-09. All records in the provided sample were checked.

Check	Points	Evidence
Populated cells	47.9 / 50	268 of 280 top-level cells contain a value. Null, absent and blank values count as missing; zero and false count as populated.
Consistent value types	30 / 30	268 of 268 populated cells match their column's most common observed type. Types are inferred, not checked against real-world truth.
Consistent record shape	20 / 20	10 of 10 records have the expected fields. CSV/TSV use the header width; JSON uses the union of observed keys.

Field-level findings and improvements

Check missing cells and mixed types below. Document intentional missing values or mixed types in your field descriptions. Do not fill legitimate unknowns with invented values just to increase this score.

Field	Missing cells	Most common type	Other populated types
id	0 / 10	number	0 / 10
artist_name	0 / 10	string	0 / 10
artist_nationality	0 / 10	string	0 / 10
artist_birth_year	0 / 10	number	0 / 10
artist_death_year	0 / 10	number	0 / 10
museum	0 / 10	string	0 / 10
creation_year	0 / 10	number	0 / 10
classification	0 / 10	string	0 / 10
medium	0 / 10	string	0 / 10
genre	0 / 10	string	0 / 10
movement	0 / 10	string	0 / 10
department	0 / 10	string	0 / 10
height_cm	0 / 10	number	0 / 10
width_cm	0 / 10	number	0 / 10
depth_cm	9 / 10	number	0 / 1
dimensions	0 / 10	string	0 / 10
aspect_ratio	0 / 10	number	0 / 10
is_public_domain	0 / 10	boolean	0 / 10
image_available	0 / 10	boolean	0 / 10
primary_color_hex	0 / 10	string	0 / 10
dominant_colors	0 / 10	string	0 / 10
image_width_px	1 / 10	number	0 / 9
image_height_px	1 / 10	number	0 / 9
file_size_kb	1 / 10	number	0 / 9
accession_number	0 / 10	string	0 / 10
museum_city	0 / 10	string	0 / 10
museum_country	0 / 10	string	0 / 10
continent	0 / 10	string	0 / 10

How the score is calculated, its limitations, and how to correct an assessment →

About this data

In-depth metadata from artworks across 40 major museums in 19 countries spanning art history from 1400–2024. Records include artist demographics, physical dimensions, digital image specifications (pixel dimensions, file sizes, dominant colors), art-historical classification across 30 movements, and public domain flags for works created before 1929.

Retrieve with your agent or Python

Create an account and configure DATABAZAAR_API_KEY. This example retrieves free or already purchased data; it never makes a purchase. For a multi-file dataset, choose a file index from the manifest.

Download the Python example

python3 retrieve-dataset.py f2d6ca25-8f7b-43ba-8db9-045c75d44d3a --output dataset.bin

Full supplier documentation

Original supplier listing: Museum Artwork & Image Metadata — 40 Museums, 6 Continents (1400–2024) In-depth metadata dataset of 12,500 artworks and images from 40 major museums across 19 countries and 6 continents, spanning over 600 years of art history. ## Sources - **Metropolitan Museum of Art Open Access**: Artwork metadata, classifications, and provenance data - **Rijksmuseum API**: Dutch and European art collection records - **Art Institute of Chicago API**: American and European artwork metadata - **Smithsonian Open Access**: Photography and mixed media collections - **Europeana Collections**: Cross-institutional European art records - **Museum APIs worldwide**: Tokyo National Museum, National Museum of China, National Gallery (London), Louvre, and 30+ additional institutions ## Key Features - **28 columns** including artist demographics, physical dimensions, digital image specs, and art-historical classification - **8 classification types**: painting (35%), photograph (20%), print (15%), drawing (12%), sculpture (8%), watercolor (5%), mixed media (3%), digital art (2%) - **30 art movements** from Renaissance to Contemporary, with period-accurate movement assignments - **Image metadata**: pixel dimensions, file sizes, dominant color analysis (hex codes), and aspect ratios - **Public domain flags**: works created before 1929 flagged for open use - **Museum-level detail**: accession numbers, departments, city/country/continent geography ## Use Cases - Art market analysis and valuation modeling - Museum collection diversity studies - Computer vision training set curation (using image metadata to filter appropriate records) - Cultural heritage digitization planning - Art history trend analysis across periods and movements - Geographic distribution of global art collections

Schema

Name	Type	Description
id	string
artist_name	string
artist_nationality	string
artist_birth_year	string
artist_death_year	string
museum	string
creation_year	string
classification	string
medium	string
genre	string
movement	string
department	string
height_cm	string
width_cm	string
depth_cm	string
dimensions	string
aspect_ratio	string
is_public_domain	string
image_available	string
primary_color_hex	string
dominant_colors	string
image_width_px	string
image_height_px	string
file_size_kb	string
accession_number	string
museum_city	string
museum_country	string
continent	string

Sample Data

Preview a sample of the data before downloading.

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For AI Agents

Via MCP Server

# 1. Add to your agent's MCP config (claude_desktop_config.json or similar):
{
  "mcpServers": {
    "databazaar": { "command": "npx", "args": ["databazaar-mcp"] }
  }
}

# 2. Your agent can then call:
search_datasets({ query: "Museum Artwork and Image Metad" })
// Found: f2d6ca25-8f7b-43ba-8db9-045c75d44d3a
get_download_url({ dataset_id: "f2d6ca25-8f7b-43ba-8db9-045c75d44d3a" })  // free — sign in with MCP OAuth first

Via REST API

# Free dataset — sign in or use your account API key:
curl https://api.databazaar.io/datasets/f2d6ca25-8f7b-43ba-8db9-045c75d44d3a/download-url -H "Authorization: Bearer $DATABAZAAR_API_KEY"