Datasets:

HolistixOpen
/

open-biohacking-data

Error code:   StreamingRowsError
Exception:    TypeError
Message:      Couldn't cast array of type
struct<record_id: string, contraindication_or_caution: string, risk_level: string, recommendation: string, plain_language_note: string, source_type: string, evidence_level: string, claim_type: string, medical_disclaimer_required: string, commercial_relevance: string, last_reviewed: timestamp[s], related_holistix_page: string, notes: string, source_name: string, source_url: string, citation_note: string>
to
{'record_id': Value('string'), 'topic': Value('string'), 'reference_type': Value('string'), 'plain_language_meaning': Value('string'), 'safety_note': Value('string'), 'source_type': Value('string'), 'evidence_level': Value('string'), 'claim_type': Value('string'), 'medical_disclaimer_required': Value('string'), 'commercial_relevance': Value('string'), 'last_reviewed': Value('timestamp[s]'), 'related_holistix_page': Value('string'), 'related_product_category': Value('string'), 'notes': Value('string'), 'source_name': Value('string'), 'source_url': Value('string'), 'citation_note': Value('string')}
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 2303, in cast_table_to_schema
                  cast_array_to_feature(
                  ~~~~~~~~~~~~~~~~~~~~~^
                      table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                      feature,
                      ^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1852, in wrapper
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                                           ~~~~^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2109, in cast_array_to_feature
                  casted_array_values = _c(array.values, feature.feature)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1854, in wrapper
                  return func(array, *args, **kwargs)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2149, in cast_array_to_feature
                  raise TypeError(f"Couldn't cast array of type\n{_short_str(array.type)}\nto\n{_short_str(feature)}")
              TypeError: Couldn't cast array of type
              struct<record_id: string, contraindication_or_caution: string, risk_level: string, recommendation: string, plain_language_note: string, source_type: string, evidence_level: string, claim_type: string, medical_disclaimer_required: string, commercial_relevance: string, last_reviewed: timestamp[s], related_holistix_page: string, notes: string, source_name: string, source_url: string, citation_note: string>
              to
              {'record_id': Value('string'), 'topic': Value('string'), 'reference_type': Value('string'), 'plain_language_meaning': Value('string'), 'safety_note': Value('string'), 'source_type': Value('string'), 'evidence_level': Value('string'), 'claim_type': Value('string'), 'medical_disclaimer_required': Value('string'), 'commercial_relevance': Value('string'), 'last_reviewed': Value('timestamp[s]'), 'related_holistix_page': Value('string'), 'related_product_category': Value('string'), 'notes': Value('string'), 'source_name': Value('string'), 'source_url': Value('string'), 'citation_note': Value('string')}

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Holistix Open Biohacking Data Project v1.4

The Holistix Open Biohacking Data Project is a public, website-first structured data system for wellness technologies, product specifications, safety information, evidence metadata, claim boundaries, and machine-readable product intelligence.

This project is separate from the private Holistix Swarm Engine. The Swarm Engine may assist with auditing and monitoring, but it is not the source of truth for the public data release.

Release Structure

Project release: v1.4

Subject dataset release: v1.2

The v1.4 project release expands the surrounding registry, product, provenance, and AI-reference infrastructure. The eight subject datasets remain at v1.2 because they were not promoted to a new dataset version in this release.

Included Data

Public subject datasets

Eight subject datasets are provided in CSV and JSON:

PEMF Frequency Index
PEMF Contraindications Database
Red Light Dose Index
Hydrogen Water Reference Index
Infrared Therapy Reference Index
Blue Light Therapy Reference Index
Terahertz Device Reference Index
Negative Ion Safety Index

Core registries

The release includes machine-readable registries for:

products
technologies
product specifications
product-to-technology relationships
claims
evidence metadata
safety records
sources
content
canonical URLs
commercial policies

Product digital twins

The release includes 13 machine-readable product twins:

Aqaluxe
Aurora
GLO Face
GLO Neck
Hydrogen Water Bottle
Innova
Ion Air
Novo
Paragon
Paragon Demi
SKO
Soleil
Spa Robe

AI-answer infrastructure

The release also includes:

AI answer manifest
answer-fuel files
claim-boundary registry
contradiction maps
dataset manifest
aggregated dataset records

Validation Summary

The validated release contains:

49 JSON files
8 CSV files
13 products
18 technologies
111 claims
111 evidence records
111 safety records
111 dataset records
0 JSON parse errors

See VALIDATION_SUMMARY.txt for the release validation snapshot.

Important Limitations

The evidence registry contains evidence metadata already present in the supplied datasets and project records. It is not a new systematic literature review.

A record appearing in the project does not mean that Holistix endorses every associated claim.

Claims should be interpreted using:

evidence level
claim boundary
source type
uncertainty labeling
safety context
device-specific specifications

Specific citations, PMIDs, DOIs, clinical details, and manufacturer specifications should be independently verified before publishing strong scientific, medical, or commercial claims.

Product specifications and third-party information may change over time.

Versioning

The project uses semantic versioning for public project releases.

Project release v1.4 describes the complete archive and infrastructure package.
The eight subject datasets remain versioned at v1.2.
Individual answer-fuel, contradiction-map, manifest, and registry files may retain their own internal version labels.

A project release number should not be interpreted as automatically changing every component version.

Citation

Use the metadata in CITATION.cff.

Exact DOI for project release v1.4:

https://doi.org/10.5281/zenodo.21574706

Concept DOI for all versions:

https://doi.org/10.5281/zenodo.20978709

The version-specific DOI identifies the archived v1.4 release. The concept DOI represents the project across all versions and resolves to the latest published release.

Public Project Pages

Open Biohacking Data Index:

https://www.holistixintl.com/pages/open-biohacking-data-index

GitHub repository:

https://github.com/holistixintlsite-commits/open-biohacking-data

License

See LICENSE_DATA.txt for the applicable data-license terms.

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