Arctic Tracker / Dataset
Dataset
The underlying tables for this site, as a frozen deposit package. These are the version-of-record files a DOI would point at. They are not generated on request: each download is a byte-identical copy of the deposit built from schema arctic_v2.
How this page was produced derived
Every file below is served from the deposit archive under public/deposit/. Row counts, byte sizes and SHA-256 digests come from MANIFEST.sha256.json. A digest is shown only when the on-disk file hashes to the manifest value.
Downloadable tables derived
100 files: 24 verification files, 22 data tables, 19 top-level documents, 12 figures, 11 supplementary tables, 10 curated sources and 2 identifier lists. 175.4 MiB carrying 500,125 rows. Verify a download against the digest in its row, which opens in full when you focus it, or take all 100 at once: checksums.sha256 is the list in the format sha256sum -c reads.
| File ↑ | Rows | Size | SHA-256 |
|---|---|---|---|
Data tables · 22 tables/ | |||
cites_listing_events.csv | 290 | 86.6 KiB | 83e5e2a5cf141226cc972bf7fe922b12ddc68945d0538e0d5c1dda144d954f3b |
cites_listings.csv | 62 | 20.3 KiB | 73dc0c9c62ee617b9687b856f3ed658bd523f5f9b51ead37e768a90106e9e2fd |
cites_trade_records.csv | 492,095 | 170.7 MiB | ca9adb6d9b9d6783eb575e3d06ed2d7d180a6c4609c6dc2bf1afb4661cf27cd4 |
cms_listings.csv | 92 | 55.5 KiB | a39825315ace1e3631741c1e21e232516b434db5481284d1f92e63f55a8262d5 |
common_names.csv | 327 | 84.6 KiB | c441a1c974142af64a37905b1a91febd6e4fbd06c8bf82a21ec78d3f3f56af34 |
conservation_profiles.csv | 4 | 4.3 KiB | 44507def3be827d29209fead1b1cd4866c64b0b3457973124e9a0eac8c8c329b |
countries.csv | 20 | 4.4 KiB | fe2a16f7c98f17977a650fac46912a97ac2753cd78e27df55cbd0759073705ec |
glossary_terms.csv | 72 | 25.5 KiB | 7abc8fe408c2230457eeed1d3f74f24f42586bfbac1cb6f5358f670fdf774512 |
illegal_trade_products.csv | 60 | 17.2 KiB | b6ff87f496ef4c887134b0f92995a59d4bcc3094ca88ecac539dd84a4019498d |
illegal_trade_seizures.csv | 225 | 89.0 KiB | 2ffc23af56b1ddd74b9c506bf143c3e7b4d5e9254983363770a041769aea8290 |
management_areas.csv | 32 | 8.2 KiB | e36ecfb5b5da1e77406161bef6d837a51cbae8bab090fd393785f75a4351d79d |
narrative_review.csv | 0 | 55 B | 1c4d992a1af617ceb15e4352de3c10d20656cff870e7a1dc3b9052d80db3ac84 |
profile_references.csv | 4 | 652 B | 54662963a79668315aa1d7c933a51472e341b64595d4628bc9cdf5c5b6267ab2 |
profile_review.csv | 0 | 53 B | 71402fa8b22287d75a6617786c88ecff537de3cd5f85d096e48e9405cacc231f |
references.csv | 4 | 2.7 KiB | 1f4243b72500e4587da9edbec9284d6979597d1e8aaaeefd87c564f3129f87b2 |
source_releases.csv | 6 | 3.1 KiB | 5f247c9a38d60d8abb98668d3b93cda2fd69f32fc9079137e0c46a657130e082 |
species.csv | 43 | 15.5 KiB | a87f6550331601c60482e7fded1ae6d3e0c9a143eb125a7f1d84295930bd8389 |
species_media.csv | 43 | 24.7 KiB | 3af1c35ff22db8e9cc71184865fea5d2042e0f0e777d7ec0c9cceae48504b67d |
species_narratives.csvUnreviewed machine-generated text, not findings. Present for completeness and audit. The site does not display these 343 sections because no subject expert has reviewed them; withholding them from the archive would be worse. | 343 | 255.1 KiB | b3b1e6c51ff3e85a9c005bcd1c7ede04f95d0ed99a7ae1f484bbe46d827c4f06 |
split_listings.csv | 2 | 783 B | ab5e8220431447ce00a51c2a46e6a2d7ee2581d5844bc6c8414f27d248c452bd |
subpopulations.csv | 12 | 3.5 KiB | dbc237e4a8a66c00d72baaefaf6ce092f7992e088f166eb8e7a6c6ddee28b51b |
timeline_events.csv | 520 | 230.8 KiB | 62e192ce651d92a1d5a40f7cfb17ac0f6fde4c15249c7b3084f75d229f446e23 |
Curated sources · 10 sources/ | |||
cites_listings.csv | 62 | 7.5 KiB | 70837666920f91ce1d571c26fdd90fdb78a16fe4d8de56d2aee3371b58bec9ff |
common_names.csv | 327 | 16.6 KiB | b108d3e6b69acebe1f7839034cf0bfdd1e2b585c565b7f24c5d741e915f66cf8 |
countries.csv | 20 | 730 B | 8b91a1a0fb94fba1436538bcf8fe2c123e172e3620c2c9bdae31f42a532c6a72 |
glossary_terms.csv | 72 | 10.7 KiB | 4eefda2f1ab9aadaf34f2335338c917f794cc5643b107647ee67f07899e415f9 |
illegal_trade_products.csv | 60 | 3.3 KiB | c6933c1defeebe4f72bb8fe47a7ee0222e8773c0e6a3aa6dcc50f60ad0ab0609 |
management_areas.csv | 32 | 1.2 KiB | c5443bb1b3bb65fb151121fa25366e3c8a6e62a0c3cbd1c2655f5f9ffb844aff |
species_taxonomy.csv | 43 | 7.2 KiB | acc358d7e9116e90475ad6a0e3a3bda4c22933d700a1d5cf547b9af8e1e1837e |
split_listings.csv | 2 | 308 B | 87babbdcc3ff45be4c00058bd9703ed52bbe13b461ebc414acac5559d68a4d53 |
subpopulations.csv | 12 | 964 B | 9bdd6a1cbf40df28c54a146611d35865aa9fb63e2861da019777fbb4845c85c1 |
timeline_events.csv | 520 | 120.8 KiB | 0e687ee40713dbace5b321a3387f899de7d6a095ac93599f5c718aa896033850 |
Identifier lists · 2 identifiers/ | |||
catch_record_ids.csv | 958 | 75.4 KiB | 536b8c46ae5ccf035a945ec1ca4df6beed57d46f64c69444d8982b94512ab2db |
iucn_assessment_ids.csv | 370 | 34.7 KiB | 11cb5f91f7cc99f0f020bbbbf0c34a5904912c72f9e3820f1ff07e42ed72d820 |
Supplementary tables · 11 supplementary/ | |||
change_table_published_vs_current.csv | 8 | 896 B | e307dff5e069a9b34cfaa7b78da951ff75490a84d6f4b5ab33dc9cb7731399e6 |
change_table_published_vs_current.md | — | 2.0 KiB | 6bf5e7b6fc5915586d73601a449a30c6d66a3818ac0c5f03ff7c2bf4f46fdffa |
README.md | — | 4.0 KiB | 36f9419572019526eda028c8ff0141ae988abb65f3eac141fe828b3f0373c11f |
species_narratives_no_citations.csv | 343 | 171.7 KiB | b37ee116eaf0c8b9f0d432de7ba1d025a79e9721952100eda4d9203270881d97 |
supplementary_table_1_post_listing_window.csv | 43 | 5.3 KiB | 691700d4612bf80e59971e7e611ae3528845ac3d5b5cb2d66cbc56ad31762dd8 |
supplementary_table_4_step_question_mapping.csv | — | 753 B | 02dba91223918b7c76343fd26b6ac227205f879522165d1455f9c4c625c931d2 |
supplementary_table_4_step_question_mapping.md | — | 1.2 KiB | 9dd5baf483016a2a4dbe6df10c53710fc2acf5af9be241804fadad7b29d14e04 |
supplementary_table_6_reporter_side_series.csv | 2,654 | 88.6 KiB | e1d32b5967095f4c2c44fe8a4750cc6e4179f6614a29191bb465e29033317153 |
supplementary_table_7_ai_toolchain.csv | 3 | 761 B | ae462eadf113978ae6c0fc84dd24e461abd6406e6d5818c6841543aa17842a1b |
supplementary_table_8_focal_set_reconciliation.csv | 6 | 129 B | 7161407fdf627803972c0672c6292a83714591b00d0312a8de2042a9350506f2 |
supplementary_table_9_quantity_by_unit_dimension.csv | 334 | 8.8 KiB | c24ce3fb40418d8500108c41c39a1ab01ada3909035a4be63e865132ce52523c |
Figures · 12 figures/ | |||
figure11-status-patterns-journal.png | — | 388.8 KiB | a2f44e71538a7d4878e3906a19efa8000e4bf3fcfc05ba1dad4707157f3af636 |
figure11-status-patterns-journal.svg | — | 12.0 KiB | 8bd0969ce13117a1ca87dd5ae740204b21fd433329757ab1561ac9179dfb1a1f |
figure12-audit-questions-journal.png | — | 729.4 KiB | 79dbd2a00bd092f750aa92b347a09ae57e11e446be7039a0ee6ef37e5a3b5e77 |
figure12-audit-questions-journal.svg | — | 12.6 KiB | 2fa0b3ecc6b1e5d4091bc838f00633a863d099a806c9286cd52450a523975b94 |
figure13-caption.md | — | 1.1 KiB | ed1ea9fada6b255111bfc4b7326d69bea9931ad304f271da9deb4fd09ba5acd8 |
figure13-pipeline-journal.png | — | 1017.3 KiB | 943a2c44454f1a97f6faaedd16c3af43ed0a1e2c6bf69906f7bdd573c99fecfc |
figure13-pipeline-journal.svg | — | 20.5 KiB | c71964545264f74d3bc90425400e71b7f1dd6966ab1971fe5824de854ff9db95 |
figure8-seizures-journal.svg | — | 16.5 KiB | 75fb534986cd8fc46cd6579c433b1064c075b119c2c962742679edb63707f730 |
pipeline-stage1.png | — | 140.8 KiB | 6566df9ba70b32141fa9f8a3ecd46b07bc75ed9d927eb6c21aab9b44d9cd383e |
pipeline-stage1.svg | — | 20.8 KiB | b65cecabde2ea04df4f96635e1bbfc055c81769b0d75e1df03919f2682bb4eae |
pipeline-stage2.png | — | 147.1 KiB | 3327411247f79e40d248e16be33e5785d27cd4136e0c4374675c77a2730dda84 |
pipeline-stage2.svg | — | 22.8 KiB | 1e996a7d4c997d06cf83142f49f7fadfeedcc2aba56f7050da7fc36110d83877 |
| Top-level documents · 19 | |||
ADDITIONS.json | — | 12.9 KiB | 2dabc21ced2f8dea2606ee43f4726f3c84cdb898b4fe4fd6795c6b1e00ead21f |
build_figure11_journal.py | — | 9.2 KiB | 0ce850c752c03fc12166dbeafcc9b756c1b7aca9477ca2aa8b02c24ba7da423b |
build_figure12_journal.py | — | 12.8 KiB | 01a96d8e9653004521a108d02def38c9ed1e6a61e5973b9a62bdd56d5c793451 |
build_figure13_journal.py | — | 17.0 KiB | d17d1003e8ae3f12ae8b3c2fa23d85d07b423a0e1fbaae47af83cfcff5cd1c32 |
build_figure8_journal.py | — | 9.2 KiB | 7f3af7fedcdce849ad472b2b0894bffdff36d226b0141cb6252160d8f8ce547e |
build_pipeline_diagram.py | — | 20.9 KiB | 7cc6168358204e0c3c49ea5f9b771069b28464ba0824ab23a3f48770e9090d2e |
build_supplementary_table_7.py | — | 7.9 KiB | 24f79fb7afd8887bc860bc4333ce1c62a25cfd1abcfbf888831ee4d16df77cfe |
data_dictionary.json | — | 40.0 KiB | 08c6fd6bad91554b979ae980e477734e1ebffaf05bc6382197c8bb8299efb9d2 |
LICENSE | — | 1.2 KiB | d3596985739261067d6409b4d62f3b25258cc5dfdfc9f8a527c1791038f0a432 |
load_deposit.sh | — | 3.1 KiB | 7ee4c837648242dfa613deff81dc8210e4f54c553f3d0c0a9f1c011ca0aeca1f |
pipeline.json | — | 7.6 KiB | 64577729e4616ecbeb2216f64578d4d133f009d69b08396c8669bc10a8bcb184 |
README.md | — | 9.6 KiB | 2a592b997de076a41c6a3657aa67243f84ff587917c14cbb4eefa17d6b3383e4 |
rebuild_iucn.py | — | 12.9 KiB | 4af88b636f7e2c7863dbd40731e1d73c5ddbcc6f5d985fc9111af366dbe75aca |
REBUILD-IUCN.digest | — | 118 B | 5cff340ec1791fcedbac05cd34841ad6cc2d0e416bd516730a166c5b777a4844 |
REBUILD-IUCN.md | — | 5.3 KiB | 62db961394a666f662525193bf70371d348773c71469d6fb737b6506a3995a5c |
results_traceability.csv | — | 118.7 KiB | 6fc2c5331be023f82b822815c832b0f0e482e0b944ec6772976bf82692045b89 |
results_traceability.md | — | 123.5 KiB | a2a5a6e86bc72c12dfac077d6319d6ad7b5f0255772ef3e0d4d40761572b2beb |
schema.sql | — | 44.1 KiB | 81f8e2f4edb68665f7e9aa00ed6927547aee7de19073e491c372f4cfc1c79cf3 |
source_data.zip | — | 15.4 KiB | 3558736147e731a25c113309a5af49e534421701d97c1324ddf703aed3d45266 |
Verification files · 24 verification/ | |||
attribution_loss.py | — | 5.5 KiB | 4948d547097d95a3c0eabb1ebe0cf39eff1d13f8f0824f1a461a613e7340300e |
check_app_numbers.py | — | 9.1 KiB | d7e52f137c3b9496ebad3c0cc2b903ec597b8dc4aa75e47b7f46a7836b3ddb02 |
check_supplementary_tables.py | — | 4.6 KiB | 6f3cbcd8b65ae8aa1c247fc7d2d7febd1dc892e9513da2f2afb8df4c1a183ae4 |
coverage_report.py | — | 11.9 KiB | 708769cdbe7a1cce8c1bdbcb38c0bbae415578f31ef64602d83a8e72026d9dd8 |
db.py | — | 4.3 KiB | 9a189832730332a266e5322109ea0fd7ede7d65a7d1b54edba8ec090030a069b |
iucn_series.py | — | 1.9 KiB | f0881642560c5246c17d1d16d2d8e8a1d5a8db4a6daaa63dae2848698f6f56ee |
README.md | — | 2.8 KiB | 76925aa4a900c993a1e42b56be8c9e9f1eba68f60897918e37922ffbad0bd6b7 |
redlist_scale.py | — | 21.2 KiB | e979fb1aae4ea9bb8524f1b0c98aafa7b34731bd5d70147c3ef19a8ce99b08d5 |
attribution_loss.json | — | 9.8 KiB | 5c4cbd70b0f77560364cdc83c7696305a7db4d5702a5c6b5795d6a46b122ede1 |
run_all.py | — | 8.1 KiB | 170409784c36b34e079e1d3203708af2bb84cf7edc4b24d7e04dbaa436721dcf |
stratify_trajectories.py | — | 9.7 KiB | 96bce389a225e3649ebc02488acfb1c8bcde04400dbb1ea658c9b5dd45278d43 |
trajectory_report.py | — | 4.0 KiB | 096b6500091074101d852a13236bca189b2d78435016b379698422e326df686b |
verify_claims_offline.py | — | 69.0 KiB | b4a7fca110b24cba8cc43424f45e556532298d09f844c45790256f907ba207f4 |
verify_deposit_roundtrip.py | — | 6.3 KiB | cf39d5ebc161c734a5a06fb95d30e5765f8b05c39d78e1eba4941e8a89373dcb |
verify_derived_truth.py | — | 22.9 KiB | 8fab6045872c54c0954cff8764051afe3c93a005a8ac4a17cc1f8e2dd8dfdd98 |
verify_flag_invariants.py | — | 15.8 KiB | feb1857efd0d5bf658ca717713a92fa81d6af9267f0442ad9653c6bf3d396a40 |
verify_iucn_withheld.py | — | 10.3 KiB | fb370f006880fa4c3da39d6c20395311eceee4d80a3009ad3b1e900dae716244 |
verify_manuscript_claims.py | — | 41.8 KiB | e453fdc6e33f480015b1f0668313388065384c74edf7acdbfac532511ea0c437 |
verify_metamorphic.py | — | 10.9 KiB | 64638802f9dfb9c4ec4d000d9aed917a571a84fe0a24b18745627b6d830b183e |
verify_pipeline_record.py | — | 7.4 KiB | 3be37eed2bc7e244dc71e99cfcdb68d24cfb0e62a65641c7612c8714ea735bc4 |
verify_schema_applies.py | — | 6.6 KiB | 1ab355aae05e5283ade6cf56a88abd34cef36372a1503250b6c345013050af7d |
verify_source_truth.py | — | 11.8 KiB | f04e859929a7af6cc9d433c26f868024bf2d1d770ef98b1a913a258f7204978a |
verify_trajectories_offline.py | — | 21.8 KiB | 91349630b147cddb127419fde46fb4fa73fed3112d2b3c3620408a8da4353e1b |
window_sensitivity.py | — | 8.6 KiB | 9cfa6354d40e4406c2d5a1e1164085c147854bcf69f47fb11889c89d58ebe184 |
The package also carries the index of itself, which is why neither is one of the 100: MANIFEST.sha256.json · checksums.sha256.
Not redistributed, and why curated
Two tables are listed here rather than omitted, and rather than redistributed in breach of their licences. Stating the withholding is a better answer than a silent gap.
iucn_assessments, 370 rowsIUCN Red List terms do not permit redistribution. The assessment identifier, publication year and scope of every withheld row are provided under identifiers/, so any reader with a free Red List account can retrieve each assessment by its identifier and reconstruct or check the table at source. The extraction is not shipped as a one-command tool inside this deposit; it lives in the code repository, where core/iucn_client.py and core/rebuild_iucn_assessments.py query the Red List API directly. Note that ingest/iucn_load.py is a loader, not an extractor: it replays a snapshot we may not redistribute, and is of no use here.
Record identifiers, without redistributable content values, are provided: iucn_assessment_ids.csv.
To rebuild this table yourself, run
core/rebuild_iucn_assessments_validated.pyfrom the code repository (Arctic-Tracker-API, private until publication) against the identifiers above. This queries the IUCN Red List API directly and rebuilds the table from the assessment identifiers below. It is the extraction path, not the loader: ingest/iucn_load.py replays a frozen snapshot CSV that we are not permitted to redistribute, so it is of no use to an outside reader.catch_records, 958 rowsNAMMCO publishes no licence or terms for the Catch Database, so no redistribution is granted. The catch_total column is the source's CATCH TOTAL for one row, in animals; the source lists national totals beside its area rows, so a sum over rows counts those animals twice. Record identifiers are provided under identifiers/. There is no extraction script: these catch figures were taken from the publicly browsable NAMMCO catch database by a scraper that was lost in an October 2025 repository cleanup. The values remain checkable at source using the identifiers and the access date; our route to them is not reproducible, and we state that rather than implying otherwise.
Record identifiers, without redistributable content values, are provided: catch_record_ids.csv.
This table cannot be regenerated from our code. We have no extraction script to offer for this table. The catch figures were taken from the NAMMCO catch database by a browser-driving scraper on 2025-06-11, and that scraper was lost in a repository cleanup in October 2025. The record identifiers below, the access date, and the documented coverage bounds are what we can give; the NAMMCO catch database is publicly browsable, so the figures are checkable at source even though our route to them is not reproducible. Saying this is better than linking to the loader, which only replays a CSV a reader cannot obtain.
How to cite this dataset curated
No DOI has been minted for this package yet. The BibTeX below uses an explicit placeholder rather than inventing one. Replace DOI-NOT-YET-MINTED when Zenodo issues the identifier.
@dataset{arctic_tracker_deposit,
title = {Arctic Tracker: trade, catch and conservation-status data for CITES-listed Arctic species},
author = {{University of Akureyri}},
year = {2026},
version = {1.0},
publisher = {Zenodo},
note = {DOI not yet minted. Deposit package built 2026-09-01 from schema arctic_v2.},
doi = {DOI-NOT-YET-MINTED}
}