---
title: "Crystallography Open Database"
description: "Every released entry of the Crystallography Open Database (COD): experimentally determined crystal structures of minerals, inorganic, metal-organic and organic compounds, one row per COD entry. Metadata for every entry: formula, cell, space group, temperature and pressure, R factor, method, and the "
url: "https://ouro.foundation/datasets/mmoderwell/crystallography-open-database"
id: "01a15c82-afe9-73cc-b0de-759388e72f42"
type: "dataset"
---

# Crystallography Open Database

Dataset by @mmoderwell in #materials-science (all) · 535,479 rows · 42 columns

- Asset id: `01a15c82-afe9-73cc-b0de-759388e72f42`
- Page: https://ouro.foundation/datasets/mmoderwell/crystallography-open-database

Every released entry of the [Crystallography Open Database](https://www.crystallography.net/cod/) (COD): experimentally determined crystal structures of minerals, inorganic, metal-organic and organic compounds, one row per COD entry.

- **Metadata for every entry:** formula, cell, space group, temperature and pressure, R factor, method, and the paper it was published in (journal, year, DOI).
- **The CIF itself for inorganic entries** (no carbon-hydrogen compounds), as COD publishes it; the few largest lose the reflection data and SHELX files embedded in them. `reduced_formula`, `num_atoms` and `primitive_atoms` (sites in its primitive cell) describe that CIF as pymatgen reads it.
- `experimental` is false for COD's few structures from calculations. `duplicate_of` and `status` (retracted, warnings, errors) are COD's own.
- `url` opens the entry on COD.

Ouro's Crystal DB novelty check matches structures against these CIFs alongside Materials Project, Alexandria and GNoME.

COD's data is in the public domain (CC0). Please acknowledge the original authors of each structure and cite COD: Gražulis et al., *J. Appl. Cryst.* 42, 726 (2009), [doi:10.1107/S0021889809016690](https://doi.org/10.1107/S0021889809016690).

## Columns

| Column | Type | Notes |
| --- | --- | --- |
| a | double precision |  |
| alpha | double precision |  |
| authors | text |  |
| b | double precision |  |
| beta | double precision |  |
| c | double precision |  |
| cell_volume | double precision |  |
| chemical_name | text |  |
| chemsys | text |  |
| cif | text |  |
| common_name | text |  |
| deposited | text |  |
| disordered | boolean |  |
| doi | text |  |
| duplicate_of | bigint |  |
| experimental | boolean |  |
| first_page | text |  |
| formula | text |  |
| gamma | double precision |  |
| has_coordinates | boolean |  |
| id | bigint | primary key |
| journal | text |  |
| journal_volume | text |  |
| method | text |  |
| mineral | text |  |
| nelements | bigint |  |
| num_atoms | bigint |  |
| organic | boolean |  |
| pressure_kpa | double precision |  |
| primitive_atoms | bigint |  |
| r_factor | double precision |  |
| radiation | text |  |
| reduced_formula | text |  |
| revision | bigint |  |
| space_group | text |  |
| space_group_number | bigint |  |
| status | text |  |
| temperature_k | double precision |  |
| title | text |  |
| url | text |  |
| year | bigint |  |
| z | double precision |  |

## First 5 rows

The first 10 of 42 columns. Query for the rest.

| a | alpha | authors | b | beta | c | cell_volume | chemical_name | chemsys | cif |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 7.8783 | 90 | Phan Thanh, S.; Marrot, J.; Renaudin, J.; Maisonneuve, V. | 10.4689 | 95.147 | 16.068 | 1319.9 |  | Al-C-H-N-O-P |  |
| 48.48 | 90 | Bachet, Bernard; Soyer, Alain; Billy, Isabelle; Mornon, Jea… | 21.72 | 90 | 10.74 | 11309.1 |  | C-H-N-O |  |
| 6.341 | 90 | Vanhoyland, G.; Bourée, F.; Van Bael, M. K.; Mullens, J.; V… | 16.88 | 97.6 | 5.7798 | 613.2 |  | C-D-O-Sr |  |
| 7.9661 | 90 | G. Vanhoyland; M.K. Van Bael; J. Mullens; L.C. Van Poucke | 9.205 | 102.104 | 7.3198 | 524.8 |  | C-O-Sr |  |
| 9.899 | 103.442 |  | 11.729 | 96.291 | 12.259 | 1364.9 |  | C-Cu-H-I-P |  |

## Query it

Read-only SQL, with `{{table}}` standing for this dataset's table.

From an agent connected to Ouro MCP:

```
query_dataset(dataset_id="01a15c82-afe9-73cc-b0de-759388e72f42", sql="SELECT * FROM {{table}} LIMIT 20")
```

From Python:

```python
df = ouro.datasets.query("01a15c82-afe9-73cc-b0de-759388e72f42", "SELECT * FROM {{table}} LIMIT 20")
```