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Datasets:
edithatogo
/
opramachine-archive-us-nj

Tasks:
Text Retrieval
Languages:
English
Tags:
public-information
freedom-of-information
government-transparency
alaveteli
web-archive
warc
License:
Dataset card Files
xet
 Community
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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
extracted_record_count: int64
generated_at: string
input_record_count: int64
input_sha256: string
instance_id: string
processed_record_count: int64
records: list<item: null>
  child 0, item: null
schema: string
replay_delay_seconds: int64
replay_limit_per_instance: int64
artifacts: list<item: struct<byte_count: int64, name: string, sha256: string>>
  child 0, item: struct<byte_count: int64, name: string, sha256: string>
      child 0, byte_count: int64
      child 1, name: string
      child 2, sha256: string
manifest_sha256: string
status_artifact: string
replay_timeout_seconds: int64
source: string
to
{'artifacts': List({'byte_count': Value('int64'), 'name': Value('string'), 'sha256': Value('string')}), 'generated_at': Value('string'), 'instance_id': Value('string'), 'manifest_sha256': Value('string'), 'replay_delay_seconds': Value('int64'), 'replay_limit_per_instance': Value('int64'), 'replay_timeout_seconds': Value('int64'), 'schema': Value('string'), 'source': Value('string'), 'status_artifact': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 149, 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 129, 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 489, 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 2818, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, 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 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              extracted_record_count: int64
              generated_at: string
              input_record_count: int64
              input_sha256: string
              instance_id: string
              processed_record_count: int64
              records: list<item: null>
                child 0, item: null
              schema: string
              replay_delay_seconds: int64
              replay_limit_per_instance: int64
              artifacts: list<item: struct<byte_count: int64, name: string, sha256: string>>
                child 0, item: struct<byte_count: int64, name: string, sha256: string>
                    child 0, byte_count: int64
                    child 1, name: string
                    child 2, sha256: string
              manifest_sha256: string
              status_artifact: string
              replay_timeout_seconds: int64
              source: string
              to
              {'artifacts': List({'byte_count': Value('int64'), 'name': Value('string'), 'sha256': Value('string')}), 'generated_at': Value('string'), 'instance_id': Value('string'), 'manifest_sha256': Value('string'), 'replay_delay_seconds': Value('int64'), 'replay_limit_per_instance': Value('int64'), 'replay_timeout_seconds': Value('int64'), 'schema': Value('string'), 'source': Value('string'), 'status_artifact': Value('string')}
              because column names don't match

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OPRA Machine public-information register

Read-only public-information request archive for https://opramachine.com (US-NJ; English). This dataset belongs to the dedicated fyi-archive collection.

Publication status

  • Instance id: us-opramachine
  • Operational status: historical-only
  • Canonical source: https://opramachine.com/
  • Dataset repository: edithatogo/opramachine-archive-us-nj

This repository is reserved for historical recovery. It is fail-closed: the card does not claim records, completeness, or live-API coverage until verified artifacts are published.

Provenance and acquisition modes

The orchestration source is edithatogo/fyi-archive. Capture is read-only, rate-limited, independently checkpointed per site, and performed through publicly available source interfaces and archival evidence. Configured source modes:

  • atom_feed
  • internet_archive
  • official_dataset
  • operator_export

Intended use

Public-interest and policy research, journalism, reproducible historical preservation, and transparency analysis. This archive is not a certified legal record, legal advice, or a substitute for the upstream site.

Data availability and loading

The repository card is always published before archive payloads. A Dataset Viewer configuration is added only when a verified Parquet manifest exists. Until then, inspect the repository without assuming a split:

from huggingface_hub import HfApi

files = HfApi().list_repo_files("edithatogo/opramachine-archive-us-nj", repo_type="dataset")
print(files)

After manifests/latest_manifest.parquet is published and verified, it can be queried with DuckDB or loaded explicitly as Parquet. The canonical manifest contract is schemas/manifest.schema.json; source-specific unavailable values remain null rather than being inferred.

Rights, privacy, and limitations

Public availability does not create a blanket reuse licence. Archived records retain their source rights, attribution, privacy, and takedown constraints; the repository code alone is MIT-licensed. Coverage is point-in-time and may be incomplete. No percentage coverage is claimed without a defensible source denominator. See the copyright, ethics, and notice documentation.

Citation 

@dataset{mordaunt_us_opramachine_archive,
  author = {Dylan Mordaunt},
  title = {OPRA Machine public-information register},
  year = {2026},
  url = {https://huggingface.co/datasets/edithatogo/opramachine-archive-us-nj}
}
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