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Datasets:
museado
/
smithsonian-data

Tasks:
Feature Extraction
Text Generation
Languages:
English
Size:
10M<n<100M
Tags:
museums
cultural-heritage
smithsonian
open-access
metadata
License:
Dataset card Files
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The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      JSON parse error: Column(/content/digital_assets_available) changed from string to boolean in row 13
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 174, in _generate_tables
                  df = pandas_read_json(f)
                       ^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json
                  return pd.read_json(path_or_buf, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 815, in read_json
                  return json_reader.read()
                         ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 1014, in read
                  obj = self._get_object_parser(self.data)
                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 1040, in _get_object_parser
                  obj = FrameParser(json, **kwargs).parse()
                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 1176, in parse
                  self._parse()
                File "/usr/local/lib/python3.12/site-packages/pandas/io/json/_json.py", line 1392, in _parse
                  ujson_loads(json, precise_float=self.precise_float), dtype=None
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
              ValueError: Trailing data
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 243, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 3496, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                                                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2257, in _head
                  return next(iter(self.iter(batch_size=n)))
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2461, in iter
                  for key, example in iterator:
                                      ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1952, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1974, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 503, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 350, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 177, in _generate_tables
                  raise e
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 151, in _generate_tables
                  pa_table = paj.read_json(
                             ^^^^^^^^^^^^^^
                File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: JSON parse error: Column(/content/digital_assets_available) changed from string to boolean in row 13

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Smithsonian Open Access Data

Pre-processed data dumps from the Smithsonian Open Access initiative, covering millions of objects across Smithsonian Institution museums and archives.

What is this?

The Smithsonian publishes their Open Access metadata on S3, but the raw data is split across 255 individual .txt files per unit. This dataset consolidates each unit's data into a single .jsonl.gz file for easier downloading and processing.

Files

Each file corresponds to a Smithsonian unit:

File Unit
aaa.jsonl.gz Archives of American Art
acah.jsonl.gz Archives Center, American History
acm.jsonl.gz Anacostia Community Museum
cfchfolklife.jsonl.gz Center for Folklife and Cultural Heritage
chndm.jsonl.gz Cooper Hewitt, Smithsonian Design Museum
eepa.jsonl.gz Eliot Elisofon Photographic Archives
fbr.jsonl.gz Smithsonian Field Book Registry
fsa.jsonl.gz Freer-Sackler Archives
fsg.jsonl.gz Freer Gallery of Art and Arthur M. Sackler Gallery
hac.jsonl.gz Horticulture Archives Collection
hmsg.jsonl.gz Hirshhorn Museum and Sculpture Garden
hsfa.jsonl.gz Human Studies Film Archives
naa.jsonl.gz National Anthropological Archives
nasm.jsonl.gz National Air and Space Museum
nmaahc.jsonl.gz National Museum of African American History and Culture
nmafa.jsonl.gz National Museum of African Art
nmah.jsonl.gz National Museum of American History
nmai.jsonl.gz National Museum of the American Indian
nmnhanthro.jsonl.gz NMNH - Anthropology
nmnhbirds.jsonl.gz NMNH - Birds
nmnhbotany.jsonl.gz NMNH - Botany
nmnheducation.jsonl.gz NMNH - Education
nmnhento.jsonl.gz NMNH - Entomology
nmnhfishes.jsonl.gz NMNH - Fishes

Usage 

# Clone the entire dataset
git clone https://huggingface.co/datasets/museado/smithsonian-data

# Or download individual files
wget https://huggingface.co/datasets/museado/smithsonian-data/resolve/main/nmah.jsonl.gz

# Decompress and explore
gunzip -c nmah.jsonl.gz | head -1 | jq .

Data Format

Each line is a JSON object representing a single Smithsonian record. The structure follows the Smithsonian's EDAN (Enterprise Digital Asset Network) schema.

Source

Original data from: https://smithsonian-open-access.s3-us-west-2.amazonaws.com/metadata/edan/

License

The underlying data is released by the Smithsonian under CC0.

Maintainer

Museado Foundation

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