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metadata 
license: cc-by-sa-4.0
tags:
  - chemistry
  - reactions
  - cheminformatics
pretty_name: The Open Reaction Database
configs:
  - config_name: default
    default: true
    data_files:
      - data/00/ord_dataset-00005539a1e04c809a9a78647bea649c.parquet
      - data/03/ord_dataset-0316886541d9435489859c2ad7edc863.parquet
      - data/0c/ord_dataset-0c75d67751634f0594b24b9f498b77c2.parquet
      - data/10/ord_dataset-10b940e7982c4622b1e1ac879394aba6.parquet
      - data/17/ord_dataset-172039a759a440219a68af62d203b79b.parquet
      - data/1d/ord_dataset-1d3a1a6fb70d46c084602d0688967afc.parquet
      - data/1e/ord_dataset-1ec2807f02fa4beda27d2a81b86eb843.parquet
      - data/20/ord_dataset-2038a3c967db4a32a8fbce288437e929.parquet
      - data/2b/ord_dataset-2be11f57f3304e678ea8469baf6dd1bc.parquet
      - data/2b/ord_dataset-2be30f5d8dcd471aa6ad410bdee05902.parquet
      - data/31/ord_dataset-31989f1b2b9d4885b1dd2d9982da4517.parquet
      - data/35/ord_dataset-35a5a513f1dd44a3a97c88da99f81a00.parquet
      - data/3b/ord_dataset-3b5db90e337942ea886b8f5bc5e3aa72.parquet
      - data/3b/ord_dataset-3b8a2ef300e145468579027f206a3ac8.parquet
      - data/46/ord_dataset-46ff9a32d9e04016b9380b1b1ef949c3.parquet
      - data/47/ord_dataset-47eaacc46c3a4487bbdf99adb1a15e41.parquet
      - data/4d/ord_dataset-4d431564f3ef4e9c91d8da5836f4eae6.parquet
      - data/52/ord_dataset-52bd3b0ec72c443aab113bcea09bf3f4.parquet
      - data/54/ord_dataset-5415f83da68e4797856ddd330dda5c61.parquet
      - data/55/ord_dataset-5540e162c09f4c04905ddc8ba9c931c6.parquet
      - data/55/ord_dataset-55de08a995554f558c25fc43eac62359.parquet
      - data/5c/ord_dataset-5c9a10329a8a48968d18879a48bb8ab2.parquet
      - data/5e/ord_dataset-5e8318f0dda04b398c14f4c3adfeb32c.parquet
      - data/5e/ord_dataset-5eb7f2689f4a42eba63ad9e37e49a5cd.parquet
      - data/67/ord_dataset-675eddcaa6674ce3ae61e79bbc1e1c08.parquet
      - data/68/ord_dataset-68cb8b4b2b384e3d85b5b1efae58b203.parquet
      - data/6a/ord_dataset-6a0bfcdf53a64c07987822162ae591e2.parquet
      - data/7a/ord_dataset-7acd6ad2bf4d4cff841cad008ab726d5.parquet
      - data/7d/ord_dataset-7d8f5fd922d4497d91cb81489b052746.parquet
      - data/80/ord_dataset-805ad863feef48579d95d86a728035f4.parquet
      - data/89/ord_dataset-89b083710e2d441aa0040c361d63359f.parquet
      - data/8d/ord_dataset-8d1e28ec1f6b4ee8ad372e0b5ed7a62e.parquet
      - data/99/ord_dataset-99c23cf435dc42f1af884053bc8b11c7.parquet
      - data/9b/ord_dataset-9b8aa9a7835143ef8ce3f70abfab7545.parquet
      - data/a1/ord_dataset-a12fa15d036d489c971b0b514caeae52.parquet
      - data/ac/ord_dataset-ac78456835404910b3a4c840248b6ac9.parquet
      - data/b4/ord_dataset-b440f8c90b6343189093770060fc4098.parquet
      - data/bc/ord_dataset-bc349c19b4384756a2aee8aa525b6c2a.parquet
      - data/c5/ord_dataset-c5b00523487a4211a194160edf45e9ab.parquet
      - data/c7/ord_dataset-c703268ea43a4c7e802c6048b6166b34.parquet
      - data/cb/ord_dataset-cbcc4048add7468e850b6ec42549c70d.parquet
      - data/ce/ord_dataset-ce5045aceb214cfc8bfd0ef3031e2737.parquet
      - data/d2/ord_dataset-d26118acda314269becc35db5c22dc59.parquet
      - data/d3/ord_dataset-d319c2a22ecf4ce59db1a18ae71d529c.parquet
      - data/d9/ord_dataset-d92976309c3a48a3a64a4cf5e7048086.parquet
      - data/dc/ord_dataset-dc0249930af34d17a3c76881a762aebf.parquet
      - data/ee/ord_dataset-eeba974d3c284aed86d1c1d442260a1e.parquet
      - data/fc/ord_dataset-fc83743b978f4deea7d6856deacbfe53.parquet
      - data/fe/ord_dataset-feaf1b793c6d408aaec1cac7cc3ceadc.parquet
  - config_name: uspto-grants
    data_files:
      - data/11/ord_dataset-1158e351757f315b93cbcbe7bc55f38e.parquet
  - config_name: uspto-mit
    data_files:
      - split: train
        path: data/e7/ord_dataset-e7830cd6b11158b43994ccfb5ee9acb3.parquet
      - split: validation
        path: data/54/ord_dataset-5481550056a14935b76e031fb94b88be.parquet
      - split: test
        path: data/48/ord_dataset-488402f6ec0d441ca2f7d6fabea7c220.parquet
  - config_name: ord_dataset-00005539a1e04c809a9a78647bea649c
    data_files:
      - data/00/ord_dataset-00005539a1e04c809a9a78647bea649c.parquet
  - config_name: ord_dataset-0316886541d9435489859c2ad7edc863
    data_files:
      - data/03/ord_dataset-0316886541d9435489859c2ad7edc863.parquet
  - config_name: ord_dataset-0c75d67751634f0594b24b9f498b77c2
    data_files:
      - data/0c/ord_dataset-0c75d67751634f0594b24b9f498b77c2.parquet
  - config_name: ord_dataset-10b940e7982c4622b1e1ac879394aba6
    data_files:
      - data/10/ord_dataset-10b940e7982c4622b1e1ac879394aba6.parquet
  - config_name: ord_dataset-1158e351757f315b93cbcbe7bc55f38e
    data_files:
      - data/11/ord_dataset-1158e351757f315b93cbcbe7bc55f38e.parquet
  - config_name: ord_dataset-172039a759a440219a68af62d203b79b
    data_files:
      - data/17/ord_dataset-172039a759a440219a68af62d203b79b.parquet
  - config_name: ord_dataset-1d3a1a6fb70d46c084602d0688967afc
    data_files:
      - data/1d/ord_dataset-1d3a1a6fb70d46c084602d0688967afc.parquet
  - config_name: ord_dataset-1ec2807f02fa4beda27d2a81b86eb843
    data_files:
      - data/1e/ord_dataset-1ec2807f02fa4beda27d2a81b86eb843.parquet
  - config_name: ord_dataset-2038a3c967db4a32a8fbce288437e929
    data_files:
      - data/20/ord_dataset-2038a3c967db4a32a8fbce288437e929.parquet
  - config_name: ord_dataset-2be11f57f3304e678ea8469baf6dd1bc
    data_files:
      - data/2b/ord_dataset-2be11f57f3304e678ea8469baf6dd1bc.parquet
  - config_name: ord_dataset-2be30f5d8dcd471aa6ad410bdee05902
    data_files:
      - data/2b/ord_dataset-2be30f5d8dcd471aa6ad410bdee05902.parquet
  - config_name: ord_dataset-31989f1b2b9d4885b1dd2d9982da4517
    data_files:
      - data/31/ord_dataset-31989f1b2b9d4885b1dd2d9982da4517.parquet
  - config_name: ord_dataset-35a5a513f1dd44a3a97c88da99f81a00
    data_files:
      - data/35/ord_dataset-35a5a513f1dd44a3a97c88da99f81a00.parquet
  - config_name: ord_dataset-3b5db90e337942ea886b8f5bc5e3aa72
    data_files:
      - data/3b/ord_dataset-3b5db90e337942ea886b8f5bc5e3aa72.parquet
  - config_name: ord_dataset-3b8a2ef300e145468579027f206a3ac8
    data_files:
      - data/3b/ord_dataset-3b8a2ef300e145468579027f206a3ac8.parquet
  - config_name: ord_dataset-46ff9a32d9e04016b9380b1b1ef949c3
    data_files:
      - data/46/ord_dataset-46ff9a32d9e04016b9380b1b1ef949c3.parquet
  - config_name: ord_dataset-47eaacc46c3a4487bbdf99adb1a15e41
    data_files:
      - data/47/ord_dataset-47eaacc46c3a4487bbdf99adb1a15e41.parquet
  - config_name: ord_dataset-488402f6ec0d441ca2f7d6fabea7c220
    data_files:
      - data/48/ord_dataset-488402f6ec0d441ca2f7d6fabea7c220.parquet
  - config_name: ord_dataset-4d431564f3ef4e9c91d8da5836f4eae6
    data_files:
      - data/4d/ord_dataset-4d431564f3ef4e9c91d8da5836f4eae6.parquet
  - config_name: ord_dataset-52bd3b0ec72c443aab113bcea09bf3f4
    data_files:
      - data/52/ord_dataset-52bd3b0ec72c443aab113bcea09bf3f4.parquet
  - config_name: ord_dataset-5415f83da68e4797856ddd330dda5c61
    data_files:
      - data/54/ord_dataset-5415f83da68e4797856ddd330dda5c61.parquet
  - config_name: ord_dataset-5481550056a14935b76e031fb94b88be
    data_files:
      - data/54/ord_dataset-5481550056a14935b76e031fb94b88be.parquet
  - config_name: ord_dataset-5540e162c09f4c04905ddc8ba9c931c6
    data_files:
      - data/55/ord_dataset-5540e162c09f4c04905ddc8ba9c931c6.parquet
  - config_name: ord_dataset-55de08a995554f558c25fc43eac62359
    data_files:
      - data/55/ord_dataset-55de08a995554f558c25fc43eac62359.parquet
  - config_name: ord_dataset-5c9a10329a8a48968d18879a48bb8ab2
    data_files:
      - data/5c/ord_dataset-5c9a10329a8a48968d18879a48bb8ab2.parquet
  - config_name: ord_dataset-5e8318f0dda04b398c14f4c3adfeb32c
    data_files:
      - data/5e/ord_dataset-5e8318f0dda04b398c14f4c3adfeb32c.parquet
  - config_name: ord_dataset-5eb7f2689f4a42eba63ad9e37e49a5cd
    data_files:
      - data/5e/ord_dataset-5eb7f2689f4a42eba63ad9e37e49a5cd.parquet
  - config_name: ord_dataset-675eddcaa6674ce3ae61e79bbc1e1c08
    data_files:
      - data/67/ord_dataset-675eddcaa6674ce3ae61e79bbc1e1c08.parquet
  - config_name: ord_dataset-68cb8b4b2b384e3d85b5b1efae58b203
    data_files:
      - data/68/ord_dataset-68cb8b4b2b384e3d85b5b1efae58b203.parquet
  - config_name: ord_dataset-6a0bfcdf53a64c07987822162ae591e2
    data_files:
      - data/6a/ord_dataset-6a0bfcdf53a64c07987822162ae591e2.parquet
  - config_name: ord_dataset-7acd6ad2bf4d4cff841cad008ab726d5
    data_files:
      - data/7a/ord_dataset-7acd6ad2bf4d4cff841cad008ab726d5.parquet
  - config_name: ord_dataset-7d8f5fd922d4497d91cb81489b052746
    data_files:
      - data/7d/ord_dataset-7d8f5fd922d4497d91cb81489b052746.parquet
  - config_name: ord_dataset-805ad863feef48579d95d86a728035f4
    data_files:
      - data/80/ord_dataset-805ad863feef48579d95d86a728035f4.parquet
  - config_name: ord_dataset-89b083710e2d441aa0040c361d63359f
    data_files:
      - data/89/ord_dataset-89b083710e2d441aa0040c361d63359f.parquet
  - config_name: ord_dataset-8d1e28ec1f6b4ee8ad372e0b5ed7a62e
    data_files:
      - data/8d/ord_dataset-8d1e28ec1f6b4ee8ad372e0b5ed7a62e.parquet
  - config_name: ord_dataset-99c23cf435dc42f1af884053bc8b11c7
    data_files:
      - data/99/ord_dataset-99c23cf435dc42f1af884053bc8b11c7.parquet
  - config_name: ord_dataset-9b8aa9a7835143ef8ce3f70abfab7545
    data_files:
      - data/9b/ord_dataset-9b8aa9a7835143ef8ce3f70abfab7545.parquet
  - config_name: ord_dataset-a12fa15d036d489c971b0b514caeae52
    data_files:
      - data/a1/ord_dataset-a12fa15d036d489c971b0b514caeae52.parquet
  - config_name: ord_dataset-ac78456835404910b3a4c840248b6ac9
    data_files:
      - data/ac/ord_dataset-ac78456835404910b3a4c840248b6ac9.parquet
  - config_name: ord_dataset-b440f8c90b6343189093770060fc4098
    data_files:
      - data/b4/ord_dataset-b440f8c90b6343189093770060fc4098.parquet
  - config_name: ord_dataset-bc349c19b4384756a2aee8aa525b6c2a
    data_files:
      - data/bc/ord_dataset-bc349c19b4384756a2aee8aa525b6c2a.parquet
  - config_name: ord_dataset-c5b00523487a4211a194160edf45e9ab
    data_files:
      - data/c5/ord_dataset-c5b00523487a4211a194160edf45e9ab.parquet
  - config_name: ord_dataset-c703268ea43a4c7e802c6048b6166b34
    data_files:
      - data/c7/ord_dataset-c703268ea43a4c7e802c6048b6166b34.parquet
  - config_name: ord_dataset-cbcc4048add7468e850b6ec42549c70d
    data_files:
      - data/cb/ord_dataset-cbcc4048add7468e850b6ec42549c70d.parquet
  - config_name: ord_dataset-ce5045aceb214cfc8bfd0ef3031e2737
    data_files:
      - data/ce/ord_dataset-ce5045aceb214cfc8bfd0ef3031e2737.parquet
  - config_name: ord_dataset-d26118acda314269becc35db5c22dc59
    data_files:
      - data/d2/ord_dataset-d26118acda314269becc35db5c22dc59.parquet
  - config_name: ord_dataset-d319c2a22ecf4ce59db1a18ae71d529c
    data_files:
      - data/d3/ord_dataset-d319c2a22ecf4ce59db1a18ae71d529c.parquet
  - config_name: ord_dataset-d92976309c3a48a3a64a4cf5e7048086
    data_files:
      - data/d9/ord_dataset-d92976309c3a48a3a64a4cf5e7048086.parquet
  - config_name: ord_dataset-dc0249930af34d17a3c76881a762aebf
    data_files:
      - data/dc/ord_dataset-dc0249930af34d17a3c76881a762aebf.parquet
  - config_name: ord_dataset-e7830cd6b11158b43994ccfb5ee9acb3
    data_files:
      - data/e7/ord_dataset-e7830cd6b11158b43994ccfb5ee9acb3.parquet
  - config_name: ord_dataset-eeba974d3c284aed86d1c1d442260a1e
    data_files:
      - data/ee/ord_dataset-eeba974d3c284aed86d1c1d442260a1e.parquet
  - config_name: ord_dataset-fc83743b978f4deea7d6856deacbfe53
    data_files:
      - data/fc/ord_dataset-fc83743b978f4deea7d6856deacbfe53.parquet
  - config_name: ord_dataset-feaf1b793c6d408aaec1cac7cc3ceadc
    data_files:
      - data/fe/ord_dataset-feaf1b793c6d408aaec1cac7cc3ceadc.parquet

ord-data

DOI

Getting the Data

The datasets live under data/ and are stored with Git LFS. LFS reads are redirected to the Hugging Face mirror via .lfsconfig, so dataset objects are fetched from Hugging Face's CDN rather than from GitHub's shared (and limited) LFS bandwidth. This is automatic — you do not need to configure anything.

Option 1: Clone the repository 

git clone https://github.com/open-reaction-database/ord-data.git

With Git LFS installed, this pulls every dataset object from the Hugging Face mirror and gives you the full Git history with the data in place.

Option 2: Download only the data (a subset, or without Git history) 

pip install huggingface_hub
python scripts/download_from_huggingface.py

(If you use uv, uv run scripts/download_from_huggingface.py installs the dependencies for you.)

The script mirrors the data/ directory from the Hugging Face dataset into your local checkout. Pass --allow-pattern 'data/4d/*.parquet' (repeatable) to download only a subset, or --output-dir <path> to write somewhere other than the repository root. To skip LFS entirely during the clone and fetch the data afterward:

GIT_LFS_SKIP_SMUDGE=1 git clone https://github.com/open-reaction-database/ord-data.git
cd ord-data
python scripts/download_from_huggingface.py

You can also browse and download datasets directly from the Hugging Face dataset page.

For how this LFS / Hugging Face mirror setup works (and what it means for contributors), see Git LFS and the Hugging Face mirror below.

Data Manipulation

The ord-data repository contains the Open Reaction Database (ORD) as Parquet files stored in the data directory. Each file holds one dataset: the reactions are serialized Protobuf messages (one per row) and the dataset name/description/ID travel in the file metadata, so those scalars and every reaction survive a round trip through ord_schema. (Dataset.reaction_ids, which names reactions stored outside the dataset, is not persisted — the reaction_id column is the source of truth — and a dataset with no reactions cannot be written at all.) The user can convert the data into human readable text format, *.pbtxt.

# import requirements
from ord_schema.datasets import load_dataset
from ord_schema.message_helpers import save_message

# load the parquet file as a Dataset proto
# (as_dataset materializes it; the default is a streaming DatasetView)
dataset = load_dataset("input_fname.parquet", as_dataset=True)
# save the ord file as human readable text
save_message(dataset, "output_fname.pbtxt")

datasets.load_dataset returns a DatasetView for Parquet, which takes the dataset's scalars and row count from the file footer and reads reactions on demand. (Note the name collision: ord_schema.parquet.load_dataset always materializes, which on the largest file is a silent 1.8M-reaction load rather than an error.) Iteration, len, indexing, and slicing over reactions behave like a list, so read-only code needs no change — and the USPTO grants file, 1.8M reactions in 1.1 GB, opens in milliseconds rather than deserializing up front. Two places the resemblance stops: indexing returns a freshly deserialized copy rather than a live sub-message, so mutating it changes nothing on disk, and reactions never compares equal to a list — compare against list(view.reactions). Pass as_dataset=True (above) when you need the protobuf surface: serializing or mutating the dataset as a whole. If you already hold a view, to_proto() does the same thing.

Beyond plain iteration, a view can look a reaction up by ID with get_reaction, yield IDs alone with iter_reaction_ids, and read one row group at a time with iter_reactions(row_group=...), which yields (reaction_id, Reaction) pairs rather than bare reactions. Row groups are the unit of parallelism for fanning out over a large file; view.num_row_groups gives the upper bound, and an index outside it raises IndexError.

We can also convert ORD data into JSON format.

# import requirements
import json

from ord_schema.datasets import load_dataset
from google.protobuf.json_format import MessageToJson

input_fname = "sample_file.parquet"
dataset = load_dataset(input_fname)

# take one reaction message from the dataset for example
rxn = dataset.reactions[0]
rxn_json = json.loads(
    MessageToJson(
        message=rxn,
        always_print_fields_with_no_presence=False,
        preserving_proto_field_name=True,
        indent=2,
        sort_keys=False,
        use_integers_for_enums=False,
        descriptor_pool=None,
        float_precision=None,
        ensure_ascii=True,
    )
)

print(
    f"We have converted the {input_fname} to JSON format shown as below, \n{rxn_json}"
)

Retired dataset IDs

Two datasets are consolidations of shards that were once published separately, and a consolidated output carries a new ID derived from the sorted IDs of its sources:

Dataset ID Sources
uspto-grants ord_dataset-1158e351757f315b93cbcbe7bc55f38e 489 monthly uspto-grants-YYYY_MM datasets
Training data from https://doi.org/10.1039/C8SC04228D ord_dataset-e7830cd6b11158b43994ccfb5ee9acb3 10 (N/10) shards

retired_datasets.csv maps each of the 499 retired IDs to the dataset that replaced it. Every other dataset kept its ID.

Per-reaction patent provenance for the USPTO data is on Reaction.provenance.patent, so the monthly bucket a reaction came from is recoverable from the consolidated dataset.

Git LFS and the Hugging Face mirror

Dataset files under data/ are stored with Git LFS. Clone and fork traffic was dominating GitHub's shared LFS bandwidth quota, so the repository is configured to keep that traffic off GitHub while leaving GitHub authoritative for the data:

  • Reads come from Hugging Face. .lfsconfig points lfs.url at the Hugging Face mirror, so clones and forks fetch LFS objects from HF's CDN instead of GitHub.
  • GitHub remains the source of truth. LFS objects are always written to GitHub (storage there is fine; only download bandwidth was the problem), and the mirror workflow copies them to Hugging Face after every merge to main. Hugging Face is purely a read replica — every object is always retrievable from GitHub.
  • LFS is scoped to data/ (see .gitattributes). A new dataset staged at the repository root is an ordinary Git file, so submissions can be pushed from a fork with no LFS configuration; the submission workflow turns the file into an LFS object when it moves it into data/.

For contributors

  • Submitting a new dataset: nothing special is required — stage your file at the repository root and open a PR (see CONTRIBUTING.md and the Submission Workflow).

  • Editing a file that already lives under data/ from a fork: that file is an LFS object, so point LFS uploads at your own fork once before pushing (you cannot write to the canonical repository's LFS store):

    git config lfs.pushurl https://github.com/<your-username>/ord-data.git/info/lfs

For maintainers (CI)

Freshly pushed objects are not on the Hugging Face mirror until the post-merge mirror job runs, so CI and the mirror override the read endpoint back to GitHub at runtime (git config lfs.url …):

  • validation.yml pulls only each matrix shard's objects from GitHub, sparsely, instead of the whole dataset in every job.
  • submission.yml reads from GitHub so fork and branch submissions are validated before their bytes reach Hugging Face.
  • huggingface_mirror.yml reads the to-be-mirrored objects from GitHub.

Contributing

Please see the Submission Workflow documentation. Make sure to review the license and terms of use.

Maintainer notes

Skipping the Update submission step

The submission workflow's Update submission step runs scripts/process_dataset.py --update --cleanup to assign reaction/dataset IDs and timestamps to newly submitted files and rewrite them to the canonical on-disk format. For maintainer PRs that touch dataset files but should not be re-processed this way — e.g., format conversions or mass migrations of already-finalized data — apply the skip-update-submission label to the PR. Note that the label leaves such a PR with no dataset validation inside the submission workflow: Validate submission runs only for fork PRs and for this workflow's own re-runs, so on a labeled maintainer PR both steps sit out. The corpus sweep in validation.yml covers the result on merge to main.

Converting datasets to Parquet

Published datasets are stored as Parquet only, and new submissions are written that way by process_dataset.py, so data/ holds no .pb.gz to convert. scripts/convert_to_parquet.py handles the case where one lands there anyway: it globs data/*/ord_dataset-*.pb.gz, converts each 1:1 (carrying the existing dataset_id), and refuses to overwrite an existing output whose reaction count disagrees with its input. Converting the corpus is this script's job, not a side effect of editing one dataset, which is why process_dataset.py leaves an edited file in whatever format it has.

It needs ord_schema, which comes from the pipeline dependency group. Because it reads .pb.gz content, pull the inputs first. With data/ Parquet-only the converter has nothing to do and says so — these steps are worth running only once a .pb.gz has actually appeared:

uv sync --only-group pipeline

git lfs pull --include="data/*/ord_dataset-*.pb.gz"
uv run --no-sync python scripts/convert_to_parquet.py --dry-run  # preview
uv run --no-sync python scripts/convert_to_parquet.py
git rm data/*/*.pb.gz  # keep only the Parquet versions

Commit the new .parquet files (they become LFS objects), push them (see Pushing new LFS objects), and open the PR with the skip-update-submission label. Validation runs against the full dataset on merge to main.

Pushing new LFS objects

.lfsconfig routes LFS reads to the Hugging Face mirror and deliberately sets no pushurl, so a plain push would try to upload new objects to HF — which you cannot write. Point LFS uploads at GitHub for the push, and make sure git can authenticate to github.com over HTTPS for the LFS API (the LFS endpoint is HTTPS even when your git remote is SSH). The simplest auth is the GitHub CLI:

git config lfs.pushurl https://github.com/open-reaction-database/ord-data.git/info/lfs
gh auth setup-git  # let git use your gh token for github.com over HTTPS
git push -u origin <branch>

Or, as a one-off without persisting any config:

git -c lfs.pushurl=https://github.com/open-reaction-database/ord-data.git/info/lfs \
    -c 'credential.https://github.com.helper=!gh auth git-credential' \
    push -u origin <branch>

Reads stay on the mirror; only your uploads go to GitHub. On merge to main, huggingface_mirror.yml copies the new objects to Hugging Face.

License

This repository carries two licenses, because it holds both data and code:

what license file
The datasets under data/ (and the repository metadata describing them) CC-BY-SA-4.0 LICENSE
The code under scripts/ and .github/ Apache-2.0 LICENSE-CODE

If you are using ORD data, CC-BY-SA-4.0 is the license that applies to you; it is what CITATION.cff and the Hugging Face mirror declare.

The code carries a separate license because Creative Commons licenses are not intended for software — Creative Commons recommends against it — and because the project's other code repositories, including ord-schema, are Apache-2.0.

Citation

If you use this dataset, please cite the Open Reaction Database paper:

@article{kearnes2021ord,
  author = {Kearnes, Steven M. and Maser, Michael R. and Wleklinski, Michael and Kast, Anton and Doyle, Abigail G. and Dreher, Spencer D. and Hawkins, Joel M. and Jensen, Klavs F. and Coley, Connor W.},
  title = {The Open Reaction Database},
  journal = {Journal of the American Chemical Society},
  year = {2021},
  volume = {143},
  number = {45},
  pages = {18820--18826},
  doi = {10.1021/jacs.1c09820},
}