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MatteoCodiglione
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3dont-online-data

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point-cloud

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xet

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train

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
format: string
project: struct<id: string, name: string, namespace: string, ontology: string>
  child 0, id: string
  child 1, name: string
  child 2, namespace: string
  child 3, ontology: string
points: int64
files: struct<positions: struct<file: string, dtype: string, components: int64, min: list<item: double>, ma (... 462 chars omitted)
  child 0, positions: struct<file: string, dtype: string, components: int64, min: list<item: double>, max: list<item: doub (... 4 chars omitted)
      child 0, file: string
      child 1, dtype: string
      child 2, components: int64
      child 3, min: list<item: double>
          child 0, item: double
      child 4, max: list<item: double>
          child 0, item: double
  child 1, colors: struct<file: string, dtype: string, components: int64>
      child 0, file: string
      child 1, dtype: string
      child 2, components: int64
  child 2, ids: struct<file: string, dtype: string, namespace: string>
      child 0, file: string
      child 1, dtype: string
      child 2, namespace: string
  child 3, links: list<item: struct<predicate: string, file: string, dtype: string, combos: string, nodes: int64, n_co (... 13 chars omitted)
      child 0, item: struct<predicate: string, file: string, dtype: string, combos: string, nodes: int64, n_combos: int64 (... 1 chars omitted)
          child 0, predicate: string
          child 1, file: string
          child 2, dtype: string
          child 3, combos: string
          child 4, nodes: int64
 
...
struct<file: string, format: string, triples: int64>
      child 0, file: string
      child 1, format: string
      child 2, triples: int64
card: struct<title: string, subtitle: string, domain: string, best_for: list<item: string>, summary: strin (... 128 chars omitted)
  child 0, title: string
  child 1, subtitle: string
  child 2, domain: string
  child 3, best_for: list<item: string>
      child 0, item: string
  child 4, summary: string
  child 5, show_me: list<item: string>
      child 0, item: string
  child 6, not_for: string
  child 7, source: string
  child 8, nl_queries: list<item: null>
      child 0, item: null
  child 9, sparql_queries: list<item: null>
      child 0, item: null
bytes: struct<positions: int64, colors: int64, ids: int64, link_Constitutes.gz: int64, link_Constitutes_com (... 282 chars omitted)
  child 0, positions: int64
  child 1, colors: int64
  child 2, ids: int64
  child 3, link_Constitutes.gz: int64
  child 4, link_Constitutes_combos.json.gz: int64
  child 5, link_Is_a_point_made_of.gz: int64
  child 6, link_Is_a_point_made_of_combos.json.gz: int64
  child 7, scalar_Day_Temperature.u16.gz: int64
  child 8, scalar_Night_Temperature.u16.gz: int64
  child 9, scalar_Heating_Propension_Index.u16.gz: int64
  child 10, scalar_Flooding_Risk_Index.u16.gz: int64
  child 11, graph: int64
total_bytes: int64
nodes: list<item: string>
  child 0, item: string
combos: list<item: list<item: int64>>
  child 0, item: list<item: int64>
      child 0, item: int64
to
{'nodes': List(Value('string')), 'combos': List(List(Value('int64')))}
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 544, 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 3052, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2559, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2584, 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 558, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, 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 361, 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 2381, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              format: string
              project: struct<id: string, name: string, namespace: string, ontology: string>
                child 0, id: string
                child 1, name: string
                child 2, namespace: string
                child 3, ontology: string
              points: int64
              files: struct<positions: struct<file: string, dtype: string, components: int64, min: list<item: double>, ma (... 462 chars omitted)
                child 0, positions: struct<file: string, dtype: string, components: int64, min: list<item: double>, max: list<item: doub (... 4 chars omitted)
                    child 0, file: string
                    child 1, dtype: string
                    child 2, components: int64
                    child 3, min: list<item: double>
                        child 0, item: double
                    child 4, max: list<item: double>
                        child 0, item: double
                child 1, colors: struct<file: string, dtype: string, components: int64>
                    child 0, file: string
                    child 1, dtype: string
                    child 2, components: int64
                child 2, ids: struct<file: string, dtype: string, namespace: string>
                    child 0, file: string
                    child 1, dtype: string
                    child 2, namespace: string
                child 3, links: list<item: struct<predicate: string, file: string, dtype: string, combos: string, nodes: int64, n_co (... 13 chars omitted)
                    child 0, item: struct<predicate: string, file: string, dtype: string, combos: string, nodes: int64, n_combos: int64 (... 1 chars omitted)
                        child 0, predicate: string
                        child 1, file: string
                        child 2, dtype: string
                        child 3, combos: string
                        child 4, nodes: int64
               
              ...
              struct<file: string, format: string, triples: int64>
                    child 0, file: string
                    child 1, format: string
                    child 2, triples: int64
              card: struct<title: string, subtitle: string, domain: string, best_for: list<item: string>, summary: strin (... 128 chars omitted)
                child 0, title: string
                child 1, subtitle: string
                child 2, domain: string
                child 3, best_for: list<item: string>
                    child 0, item: string
                child 4, summary: string
                child 5, show_me: list<item: string>
                    child 0, item: string
                child 6, not_for: string
                child 7, source: string
                child 8, nl_queries: list<item: null>
                    child 0, item: null
                child 9, sparql_queries: list<item: null>
                    child 0, item: null
              bytes: struct<positions: int64, colors: int64, ids: int64, link_Constitutes.gz: int64, link_Constitutes_com (... 282 chars omitted)
                child 0, positions: int64
                child 1, colors: int64
                child 2, ids: int64
                child 3, link_Constitutes.gz: int64
                child 4, link_Constitutes_combos.json.gz: int64
                child 5, link_Is_a_point_made_of.gz: int64
                child 6, link_Is_a_point_made_of_combos.json.gz: int64
                child 7, scalar_Day_Temperature.u16.gz: int64
                child 8, scalar_Night_Temperature.u16.gz: int64
                child 9, scalar_Heating_Propension_Index.u16.gz: int64
                child 10, scalar_Flooding_Risk_Index.u16.gz: int64
                child 11, graph: int64
              total_bytes: int64
              nodes: list<item: string>
                child 0, item: string
              combos: list<item: list<item: int64>>
                child 0, item: list<item: int64>
                    child 0, item: int64
              to
              {'nodes': List(Value('string')), 'combos': List(List(Value('int64')))}
              because column names don't match

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

3DOnt online — 3DGraph bundles

The data behind the online demo of the 3DGraphExplorer (3DOnt). Each folder is a 3DGraph converted for the browser: the explorer downloads it and runs rendering, SPARQL and segmentations on the visitor's machine.

folder	project	what it shows
`ytu3d/`	YTU3D	dynamic semantic segmentation S(Mr, Tr)
`ferrara/`	Ferrara	materials and expert knowledge (urban)
`neptune/`	Temple of Neptune, Paestum	heritage: column, capital, shaft, architrave, ...
`santachiara/`	Santa Chiara	dew-formation risk from sensor data streams

Format of a bundle

manifest.json: project, counts, files, quantisation;
graph.nt.gz: object-level triples and ontology (3DOntCore 1.0.0, http://3DOntCore#);
point positions (uint16-quantised), colours, point→object links and point values as gzipped typed arrays, stored in shuffled order (progressive loading).

The conversion and the standardisation of the ontologies are documented in the demo's repository (pipeline/, docs/STANDARDISATION.md).

Reference

M. Codiglione, S. Facenda, F. Remondino — Integrating ontologies and object compositional hierarchies for dynamic semantic segmentation of point clouds, ISPRS Archives L-4/W2-2026 (GeoSofia 2026), doi:10.5194/isprs-archives-L-4-W2-2026-33-2026.

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