Datasets:
Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 91, in _split_generators
pa_table = next(iter(self._generate_tables(**splits[0].gen_kwargs, allow_full_read=False)))[1]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 193, in _generate_tables
examples = [ujson_loads(line) for line in batch.splitlines()]
^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/utils/json.py", line 20, in ujson_loads
return pd.io.json.ujson_loads(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ValueError: Expected object or value
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 65, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.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.
SpaceOmicsBench v3
A Multi-Omics AI Benchmark for Spaceflight Biomedical Data
SpaceOmicsBench v3 provides standardized ML and LLM evaluation infrastructure for spaceflight biomedical data from 4 human spaceflight missions (NASA Twins Study, Inspiration4, JAXA cfRNA, Axiom-2).
Dataset Structure
ML Track (Track A)
tasks/track_a/— Task definitions (J1: phase classification, J2: clock acceleration)tasks/track_c/— Feature-level task definitions (C1: cfRNA DEG, C3: PPI benchmark)data/tasks/— Training data for J1 and J2 (n=20 samples)data/axiom2_epigenetic/— AX-2 epigenetic clock measurements (83 algorithms, 20 samples × 92 features)data/external/string_ppi/— STRING v12 PPI network topology features (17,995 genes × 4 features)results/unified_baseline_results.json— Complete leaderboard (26 tasks, 16+ baseline methods)results/track_a/— Stage-level results (TabPFN, ESM2, GNN, fusion, feature selection)
LLM Track (Track B)
tasks/track_b/— Question bank by category (12 categories, 270 questions)evaluation/llm/question_bank_v3.json— Full 270Q bank with ground truth, difficulty, uncertainty flagsevaluation/llm/annotation_schema.json— Scoring rubric and 5-dimension framework
Key Statistics
- 26 ML tasks across 9 omics modalities (19 from v2 + 7 new)
- 270 LLM evaluation questions (12 categories, 4 difficulty levels)
- 4 spaceflight missions: NASA Twins (340d), Inspiration4 (3d), JAXA cfRNA, Axiom-2
- Crew IDs: Anonymized (C001–C004 for I4, A001–A004 for AX-2)
Citation
If you use this dataset, please cite:
Jang, J. (2026). SpaceOmicsBench: A Multi-Omics AI Benchmark for Spaceflight Biomedical Data (v3).
Submitted to NeurIPS 2026 Datasets & Benchmarks Track.
GitHub: https://github.com/jang1563/SpaceOmicsBench
License
- Data: CC BY-NC 4.0
- Code: MIT License
Contact
JangKeun Kim (jak4013@med.cornell.edu) — Weill Cornell Medicine
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