Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
jurisdictions: list<item: string>
child 0, item: string
page: int64
page_size: int64
rows: list<item: struct<dimensions: struct<person.age_band: string, person.sex: string, direct: string, fr (... 2123 chars omitted)
child 0, item: struct<dimensions: struct<person.age_band: string, person.sex: string, direct: string, freq: string, (... 2111 chars omitted)
child 0, dimensions: struct<person.age_band: string, person.sex: string, direct: string, freq: string, geo: string, na_it (... 140 chars omitted)
child 0, person.age_band: string
child 1, person.sex: string
child 2, direct: string
child 3, freq: string
child 4, geo: string
child 5, na_item: string
child 6, sector: string
child 7, time: int64
child 8, unit: string
child 9, validation.metric: string
child 10, validation.series: string
child 11, spdeps: string
child 12, spfunc: string
child 1, entity: string
child 2, fact_key: string
child 3, geography_id: string
child 4, geography_level: string
child 5, label: string
child 6, ledger_source: string
child 7, measure: string
child 8, observed_period: string
child 9, observed_value: string
child 10, provenance: struct<aggregation: struct<method: string>, observed_measure: struct<source_concept: string, source_ (... 326 chars omitted)
child 0, aggregation: struct<method: stri
...
87a743c106720a792b1d185: int64
child 705, ledger.aggregate_fact.v2:f8f960b0d9e73a40a81a6dd7: int64
child 706, ledger.aggregate_fact.v2:f90bbeff6092492e180dd123: int64
child 707, ledger.aggregate_fact.v2:f9a97c5b777f5efdd9afabeb: int64
child 708, ledger.aggregate_fact.v2:f9e1abd7aaff2ee2487f8647: int64
child 709, ledger.aggregate_fact.v2:fa4b6329a67e1b5acb913bdc: int64
child 710, ledger.aggregate_fact.v2:fa76bfb900255f84b3f1458c: int64
child 711, ledger.aggregate_fact.v2:fa78795c6851c7688c7e2d5a: int64
child 712, ledger.aggregate_fact.v2:fab0e8926b2a69477fca9ede: int64
child 713, ledger.aggregate_fact.v2:fac6476a0da56862ec9d981e: int64
child 714, ledger.aggregate_fact.v2:fbcdac87dc315acb89458d99: int64
child 715, ledger.aggregate_fact.v2:fc28341f2ecceb2ab2ffbea4: int64
child 716, ledger.aggregate_fact.v2:fc3327e5ad0b7d99f9b57f7f: int64
child 717, ledger.aggregate_fact.v2:fc981e1ed0609cc26337540f: int64
child 718, ledger.aggregate_fact.v2:fd0c01f102f8ef5b80a6389b: int64
child 719, ledger.aggregate_fact.v2:fd7d85f58328ef58a5d49a44: int64
child 720, ledger.aggregate_fact.v2:fddbc0da49b6c3060b71e07e: int64
child 721, ledger.aggregate_fact.v2:fdf4de7cdbdaca72dbc8ebec: int64
child 722, ledger.aggregate_fact.v2:fe398ada3f3c2892a7c54aa6: int64
child 723, ledger.aggregate_fact.v2:fe5e64932235cabe8b8cd932: int64
child 724, ledger.aggregate_fact.v2:fe6cf36a6ddfca472335a3b8: int64
child 725, ledger.aggregate_fact.v2:fe8d456fec45507b71796fdf: int64
to
{'facets': {'geography': {'commune': List(Value('int64')), 'country': List(Value('int64')), 'nuts1': List(Value('int64'))}, 'ledger_source': {'eurostat': List(Value('int64')), 'jrc_euromod_be': List(Value('int64')), 'nbb_national_accounts': List(Value('int64')), 'onem_rva_unemployment': List(Value('int64')), 'onss_contributions': List(Value('int64')), 'sfpd_pensions': List(Value('int64')), 'statbel_fiscal_income': List(Value('int64')), 'statbel_population_structure': List(Value('int64'))}, 'measure': {'belgium_household_national_accounts_non_financial_transaction_amount': List(Value('int64')), 'belgium_pit_taxable_income': List(Value('int64')), 'belgium_worker_article_17_uncapped_component_contribution': List(Value('int64')), 'euromod_be.distribution_validation_percent': List(Value('int64')), 'euromod_be.distribution_validation_ratio': List(Value('int64')), 'euromod_be.external_macrovalidation_amount': List(Value('int64')), 'euromod_be.external_macrovalidation_recipient_count': List(Value('int64')), 'euromod_be.macrovalidation_amount': List(Value('int64')), 'euromod_be.macrovalidation_ratio': List(Value('int64')), 'euromod_be.silc_macrovalidation_recipient_count': List(Value('int64')), 'eurostat.gov_10a_taxag.revenue': List(Value('int64')), 'household_disposable_income': List(Value('int64')), 'legal_pension_recipients': List(Value('int64')), 'people': List(Value('int64')), 'receives_unemployment_benefit': List(Value('int64')), 'social_protection_expenditure': List(Value('int6
...
ate_fact.v2:f90bbeff6092492e180dd123': Value('int64'), 'ledger.aggregate_fact.v2:f9a97c5b777f5efdd9afabeb': Value('int64'), 'ledger.aggregate_fact.v2:f9e1abd7aaff2ee2487f8647': Value('int64'), 'ledger.aggregate_fact.v2:fa4b6329a67e1b5acb913bdc': Value('int64'), 'ledger.aggregate_fact.v2:fa76bfb900255f84b3f1458c': Value('int64'), 'ledger.aggregate_fact.v2:fa78795c6851c7688c7e2d5a': Value('int64'), 'ledger.aggregate_fact.v2:fab0e8926b2a69477fca9ede': Value('int64'), 'ledger.aggregate_fact.v2:fac6476a0da56862ec9d981e': Value('int64'), 'ledger.aggregate_fact.v2:fbcdac87dc315acb89458d99': Value('int64'), 'ledger.aggregate_fact.v2:fc28341f2ecceb2ab2ffbea4': Value('int64'), 'ledger.aggregate_fact.v2:fc3327e5ad0b7d99f9b57f7f': Value('int64'), 'ledger.aggregate_fact.v2:fc981e1ed0609cc26337540f': Value('int64'), 'ledger.aggregate_fact.v2:fd0c01f102f8ef5b80a6389b': Value('int64'), 'ledger.aggregate_fact.v2:fd7d85f58328ef58a5d49a44': Value('int64'), 'ledger.aggregate_fact.v2:fddbc0da49b6c3060b71e07e': Value('int64'), 'ledger.aggregate_fact.v2:fdf4de7cdbdaca72dbc8ebec': Value('int64'), 'ledger.aggregate_fact.v2:fe398ada3f3c2892a7c54aa6': Value('int64'), 'ledger.aggregate_fact.v2:fe5e64932235cabe8b8cd932': Value('int64'), 'ledger.aggregate_fact.v2:fe6cf36a6ddfca472335a3b8': Value('int64'), 'ledger.aggregate_fact.v2:fe8d456fec45507b71796fdf': Value('int64')}, 'jurisdictions': List(Value('string')), 'run_id': Value('string'), 'schema_version': Value('string'), 'snapshot_id': Value('string')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2840, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
jurisdictions: list<item: string>
child 0, item: string
page: int64
page_size: int64
rows: list<item: struct<dimensions: struct<person.age_band: string, person.sex: string, direct: string, fr (... 2123 chars omitted)
child 0, item: struct<dimensions: struct<person.age_band: string, person.sex: string, direct: string, freq: string, (... 2111 chars omitted)
child 0, dimensions: struct<person.age_band: string, person.sex: string, direct: string, freq: string, geo: string, na_it (... 140 chars omitted)
child 0, person.age_band: string
child 1, person.sex: string
child 2, direct: string
child 3, freq: string
child 4, geo: string
child 5, na_item: string
child 6, sector: string
child 7, time: int64
child 8, unit: string
child 9, validation.metric: string
child 10, validation.series: string
child 11, spdeps: string
child 12, spfunc: string
child 1, entity: string
child 2, fact_key: string
child 3, geography_id: string
child 4, geography_level: string
child 5, label: string
child 6, ledger_source: string
child 7, measure: string
child 8, observed_period: string
child 9, observed_value: string
child 10, provenance: struct<aggregation: struct<method: string>, observed_measure: struct<source_concept: string, source_ (... 326 chars omitted)
child 0, aggregation: struct<method: stri
...
87a743c106720a792b1d185: int64
child 705, ledger.aggregate_fact.v2:f8f960b0d9e73a40a81a6dd7: int64
child 706, ledger.aggregate_fact.v2:f90bbeff6092492e180dd123: int64
child 707, ledger.aggregate_fact.v2:f9a97c5b777f5efdd9afabeb: int64
child 708, ledger.aggregate_fact.v2:f9e1abd7aaff2ee2487f8647: int64
child 709, ledger.aggregate_fact.v2:fa4b6329a67e1b5acb913bdc: int64
child 710, ledger.aggregate_fact.v2:fa76bfb900255f84b3f1458c: int64
child 711, ledger.aggregate_fact.v2:fa78795c6851c7688c7e2d5a: int64
child 712, ledger.aggregate_fact.v2:fab0e8926b2a69477fca9ede: int64
child 713, ledger.aggregate_fact.v2:fac6476a0da56862ec9d981e: int64
child 714, ledger.aggregate_fact.v2:fbcdac87dc315acb89458d99: int64
child 715, ledger.aggregate_fact.v2:fc28341f2ecceb2ab2ffbea4: int64
child 716, ledger.aggregate_fact.v2:fc3327e5ad0b7d99f9b57f7f: int64
child 717, ledger.aggregate_fact.v2:fc981e1ed0609cc26337540f: int64
child 718, ledger.aggregate_fact.v2:fd0c01f102f8ef5b80a6389b: int64
child 719, ledger.aggregate_fact.v2:fd7d85f58328ef58a5d49a44: int64
child 720, ledger.aggregate_fact.v2:fddbc0da49b6c3060b71e07e: int64
child 721, ledger.aggregate_fact.v2:fdf4de7cdbdaca72dbc8ebec: int64
child 722, ledger.aggregate_fact.v2:fe398ada3f3c2892a7c54aa6: int64
child 723, ledger.aggregate_fact.v2:fe5e64932235cabe8b8cd932: int64
child 724, ledger.aggregate_fact.v2:fe6cf36a6ddfca472335a3b8: int64
child 725, ledger.aggregate_fact.v2:fe8d456fec45507b71796fdf: int64
to
{'facets': {'geography': {'commune': List(Value('int64')), 'country': List(Value('int64')), 'nuts1': List(Value('int64'))}, 'ledger_source': {'eurostat': List(Value('int64')), 'jrc_euromod_be': List(Value('int64')), 'nbb_national_accounts': List(Value('int64')), 'onem_rva_unemployment': List(Value('int64')), 'onss_contributions': List(Value('int64')), 'sfpd_pensions': List(Value('int64')), 'statbel_fiscal_income': List(Value('int64')), 'statbel_population_structure': List(Value('int64'))}, 'measure': {'belgium_household_national_accounts_non_financial_transaction_amount': List(Value('int64')), 'belgium_pit_taxable_income': List(Value('int64')), 'belgium_worker_article_17_uncapped_component_contribution': List(Value('int64')), 'euromod_be.distribution_validation_percent': List(Value('int64')), 'euromod_be.distribution_validation_ratio': List(Value('int64')), 'euromod_be.external_macrovalidation_amount': List(Value('int64')), 'euromod_be.external_macrovalidation_recipient_count': List(Value('int64')), 'euromod_be.macrovalidation_amount': List(Value('int64')), 'euromod_be.macrovalidation_ratio': List(Value('int64')), 'euromod_be.silc_macrovalidation_recipient_count': List(Value('int64')), 'eurostat.gov_10a_taxag.revenue': List(Value('int64')), 'household_disposable_income': List(Value('int64')), 'legal_pension_recipients': List(Value('int64')), 'people': List(Value('int64')), 'receives_unemployment_benefit': List(Value('int64')), 'social_protection_expenditure': List(Value('int6
...
ate_fact.v2:f90bbeff6092492e180dd123': Value('int64'), 'ledger.aggregate_fact.v2:f9a97c5b777f5efdd9afabeb': Value('int64'), 'ledger.aggregate_fact.v2:f9e1abd7aaff2ee2487f8647': Value('int64'), 'ledger.aggregate_fact.v2:fa4b6329a67e1b5acb913bdc': Value('int64'), 'ledger.aggregate_fact.v2:fa76bfb900255f84b3f1458c': Value('int64'), 'ledger.aggregate_fact.v2:fa78795c6851c7688c7e2d5a': Value('int64'), 'ledger.aggregate_fact.v2:fab0e8926b2a69477fca9ede': Value('int64'), 'ledger.aggregate_fact.v2:fac6476a0da56862ec9d981e': Value('int64'), 'ledger.aggregate_fact.v2:fbcdac87dc315acb89458d99': Value('int64'), 'ledger.aggregate_fact.v2:fc28341f2ecceb2ab2ffbea4': Value('int64'), 'ledger.aggregate_fact.v2:fc3327e5ad0b7d99f9b57f7f': Value('int64'), 'ledger.aggregate_fact.v2:fc981e1ed0609cc26337540f': Value('int64'), 'ledger.aggregate_fact.v2:fd0c01f102f8ef5b80a6389b': Value('int64'), 'ledger.aggregate_fact.v2:fd7d85f58328ef58a5d49a44': Value('int64'), 'ledger.aggregate_fact.v2:fddbc0da49b6c3060b71e07e': Value('int64'), 'ledger.aggregate_fact.v2:fdf4de7cdbdaca72dbc8ebec': Value('int64'), 'ledger.aggregate_fact.v2:fe398ada3f3c2892a7c54aa6': Value('int64'), 'ledger.aggregate_fact.v2:fe5e64932235cabe8b8cd932': Value('int64'), 'ledger.aggregate_fact.v2:fe6cf36a6ddfca472335a3b8': Value('int64'), 'ledger.aggregate_fact.v2:fe8d456fec45507b71796fdf': Value('int64')}, 'jurisdictions': List(Value('string')), 'run_id': Value('string'), 'schema_version': Value('string'), 'snapshot_id': Value('string')}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Microcosm cross-dataset evaluation bundles
Immutable frontend bundles (cross_dataset.frontend_bundle.v1) consumed by the calibration
diagnostics dashboard's Cross-dataset page: every source (a model × dataset pair, or a standalone
dataset) scored against the same Chronicle facts for a jurisdiction. Produced by
PolicyEngine/calibration-diagnostics scripts/run_full_chronicle_evaluation.py +
publish_cross_dataset_frontend_bundle.py; every partition carries the run and snapshot ids and
a SHA-256 recorded in manifest.json.
Layout: <jurisdiction>/<run_id>/frontend/ and <jurisdiction>/latest.json → run id.
Belgium (evaluation-f28ca06a0b0d2baf13c87f2f): sources Microcosm-BE v0.4 × Axiom rules engine, Microcosm-BE v0.4 × EUROMOD BE_2025, EUROMOD BE_2025 on EU-SILC (JRC country report). Microcosm-BE provenance: synthetic Belgian population calibrated to Belgian administrative and national-accounts targets (sums of Chronicle facts; surveys validation-only); support records are a US survey donor pool, reweighted; a Belgian donor pool is the planned upgrade.
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